Alternatives to Statsbot

Compare Statsbot alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Statsbot in 2026. Compare features, ratings, user reviews, pricing, and more from Statsbot competitors and alternatives in order to make an informed decision for your business.

  • 1
    Apache Doris

    Apache Doris

    The Apache Software Foundation

    Apache Doris is a modern data warehouse for real-time analytics. It delivers lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within a second. Storage engine with real-time upsert, append and pre-aggregation. Optimize for high-concurrency and high-throughput queries with columnar storage engine, MPP architecture, cost based query optimizer, vectorized execution engine. Federated querying of data lakes such as Hive, Iceberg and Hudi, and databases such as MySQL and PostgreSQL. Compound data types such as Array, Map and JSON. Variant data type to support auto data type inference of JSON data. NGram bloomfilter and inverted index for text searches. Distributed design for linear scalability. Workload isolation and tiered storage for efficient resource management. Supports shared-nothing clusters as well as separation of storage and compute.
    Starting Price: Free
  • 2
    VeloDB

    VeloDB

    VeloDB

    Powered by Apache Doris, VeloDB is a modern data warehouse for lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within seconds. Storage engine with real-time upsert、append and pre-aggregation. Unparalleled performance in both real-time data serving and interactive ad-hoc queries. Not just structured but also semi-structured data. Not just real-time analytics but also batch processing. Not just run queries against internal data but also work as a federate query engine to access external data lakes and databases. Distributed design to support linear scalability. Whether on-premise deployment or cloud service, separation or integration of storage and compute, resource usage can be flexibly and efficiently adjusted according to workload requirements. Built on and fully compatible with open source Apache Doris. Support MySQL protocol, functions, and SQL for easy integration with other data tools.
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    Cisco ASR 900 Series Aggregation Services Routers
    The ASR 900 Series is a modular aggregation platform that delivers cost-effective converged mobile, residential, and business services. You get redundancy, a shallow depth, low power consumption, and high service scale in routers packed with useful features and optimized for small aggregation and remote point-of-presence (POP) applications. Deliver a greatly enhanced broadband customer experience. This series supports broadband aggregation for voice, video, data, and mobility services. It supports thousands of subscribers, and QoS scales to a large number of queues per device. Deployed as a pre-aggregation platform for mobile backhaul, the series can aggregate cell sites and use MPLS as a transport for RAN backhaul traffic. Get the timing services required in today’s converged access networks. The series offers integrated support for a variety of interfaces and can act as the source for network clocking for GPS and other interfaces.
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    Ottava

    Ottava

    Potix Corporation

    Ottava is an intuitive data management and analysis software, seamlessly merging Excel-based workflows with advanced data analysis to cater specifically to non-technical users. It effortlessly streamlines the tasks of data input, chart creation, and analysis, marrying conventional approaches with innovative solutions for a seamless user experience. What sets Ottava apart is its ability to effortlessly handle pre-aggregated or pivoted data, making it a standout data analytics platform. In contrast to conventional tools that demand users to prepare tabular data before delving into detailed analyses, Ottava empowers users to input, explore, and extract insights directly from already pivoted or aggregated tables. This distinctive capability simplifies the analytical journey, saves valuable time, and allows users to uncover concealed patterns and valuable information within their data, facilitating more insightful decision-making.
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    Dremio

    Dremio

    Dremio

    Dremio delivers lightning-fast queries and a self-service semantic layer directly on your data lake storage. No moving data to proprietary data warehouses, no cubes, no aggregation tables or extracts. Just flexibility and control for data architects, and self-service for data consumers. Dremio technologies like Data Reflections, Columnar Cloud Cache (C3) and Predictive Pipelining work alongside Apache Arrow to make queries on your data lake storage very, very fast. An abstraction layer enables IT to apply security and business meaning, while enabling analysts and data scientists to explore data and derive new virtual datasets. Dremio’s semantic layer is an integrated, searchable catalog that indexes all of your metadata, so business users can easily make sense of your data. Virtual datasets and spaces make up the semantic layer, and are all indexed and searchable.
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    rakam

    rakam

    Rakam

    rakam provides verticalized reporting features for different teams's reporting needs so, your teams are not restricted in a single interface. rakam turns the questions you ask within user interface to SQL while hiding the complexity from the end-users. rakam doesn't load any data into your data warehouse, it expects you to have all the data inside your data-warehouse and lets you analyze the data without pulling the data outside your data warehouse, the single source of truth. Link to our blog post about the topic. rakam natively supports dbt core as the data modeling layer. rakam doesn't run your dbt transformations, instead connects to your GIT repository and synchronizes your dbt models automatically. rakam can create incremental dbt models, make use of them to speed up your queries and reduce the query costs on your database. When you define aggregates in your dbt resource files, rakam creates roll-up models programmatically hiding the complexity from end-users.
    Starting Price: $25 per user per month
  • 7
    CData Query Federation Drivers
    The Query Federation Drivers provide a universal data access layer that simplifies application development and data access. The drivers make it easy to query data across systems with SQL through a common driver interface. The Query Federation Drivers enable users to embed Logical Data Warehousing capabilities into any application or process. A Logical Data Warehouse is an architectural layer that enables access to multiple data sources on-demand, without relocating or transforming data in advance. Essentially the Query Federation Drivers give users simple, SQL-based access to all of your databases, data warehouses, and cloud applications through a single interface. Developers can pick multiple data processing systems and access all of them with a single SQL-based interface.
  • 8
    Google Cloud Datalab
    An easy-to-use interactive tool for data exploration, analysis, visualization, and machine learning. Cloud Datalab is a powerful interactive tool created to explore, analyze, transform, and visualize data and build machine learning models on Google Cloud Platform. It runs on Compute Engine and connects to multiple cloud services easily so you can focus on your data science tasks. Cloud Datalab is built on Jupyter (formerly IPython), which boasts a thriving ecosystem of modules and a robust knowledge base. Cloud Datalab enables analysis of your data on BigQuery, AI Platform, Compute Engine, and Cloud Storage using Python, SQL, and JavaScript (for BigQuery user-defined functions). Whether you're analyzing megabytes or terabytes, Cloud Datalab has you covered. Query terabytes of data in BigQuery, run local analysis on sampled data, and run training jobs on terabytes of data in AI Platform seamlessly.
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    CharityBase

    CharityBase

    CharityBase

    CharityBase is a free, open source database and GraphQL API that aggregates fragmented data from the Charity Commission, Companies House, 360 Giving, charity websites, the ONS, and social media into a single, cleaned, normalized, and searchable dataset. It powers a public search portal where users can discover detailed profiles of UK charities, complete with finance, governance, and activity data, and offers a single GraphQL endpoint that responds in structured JSON with custom queries for counts, aggregates, and detailed lists. Designed to eliminate the heavy lifting of data collection and cleaning, CharityBase enables startups, grantmakers, and researchers to build digital tools, such as dashboards, reports, and grant-finding applications, without managing their own data pipeline. Its API supports both GET and POST requests, variable-driven queries, pagination, and live interactive playgrounds for rapid prototyping, all underpinned by regularly updated, audit-trail-backed records.
    Starting Price: Free
  • 10
    Microsoft Power Query
    Power Query is the easiest way to connect, extract, transform and load data from a wide range of sources. Power Query is a data transformation and data preparation engine. Power Query comes with a graphical interface for getting data from sources and a Power Query Editor for applying transformations. Because the engine is available in many products and services, the destination where the data will be stored depends on where Power Query was used. Using Power Query, you can perform the extract, transform, and load (ETL) processing of data. Microsoft’s Data Connectivity and Data Preparation technology that lets you seamlessly access data stored in hundreds of sources and reshape it to fit your needs—all with an easy to use, engaging, no-code experience. Power Query supports hundreds of data sources with built-in connectors, generic interfaces (such as REST APIs, ODBC, OLE, DB and OData) and the Power Query SDK to build your own connectors.
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    Goldsky

    Goldsky

    Goldsky

    Check in every change you make. Swap versions via history to make sure your API’s running smoothly. With our subgraph-optimized pre-caching infrastructure, customers see up to 3x faster indexing with no code changes. Create streams with SQL from subgraphs and other streams, get persistent aggregations with no lag, and access the result through bridges. Sub-second, reorg-aware ETL to tools like Hasura, Timescale, Elasticsearch, and more. Merge subgraphs across multiple chains into one stream, and query expensive aggregations in milliseconds. Layer streams on streams, join with off-chain data, and form your unique real-time view of the blockchain. Run resilient webhooks, run analytical queries, fuzzy search, and more. Bridge streams and subgraphs to databases like Timescale and Elasticsearch, or straight a hosted GraphQL API.
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    Ocient Hyperscale Data Warehouse
    The Ocient Hyperscale Data Warehouse transforms and loads data in seconds, enables organizations to store and analyze more data, and executes queries on hyperscale datasets up to 50x faster. To deliver next-generation data analytics, Ocient completely reimagined its data warehouse design to deliver rapid, continuous analysis of complex, hyperscale datasets. The Ocient Hyperscale Data Warehouse brings storage adjacent to compute to maximize performance on industry-standard hardware, enables users to transform, stream or load data directly, and returns previously infeasible queries in seconds. Optimized for industry standard hardware, Ocient has benchmarked query performance levels up to 50x better than competing products. The Ocient Hyperscale Data Warehouse empowers next-generation data analytics solutions in key areas where existing solutions fall short.
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    Raijin

    Raijin

    RAIJINDB

    In order to deal with sparse data, the Raijin Database uses a flat JSON representation for the data records. The Raijin Database supports SQL as its primary query language while lifting some of SQL's limitations. Data compression not only saves disk space but provides a performance boost with modern CPUs. Most NoSQL solutions are inefficient at or totally lack support for analytical queries. Raijin DB supports group by and aggregations using standard SQL syntax. Vectorized execution and cache-friendly algorithms allow large amounts of data to be operated on. Backed by optimized SIMD instructions (SSE2/AVX2) and a modern compressed hybrid columnar storage layer it ensures that your CPUs are not wasting cycles. This gives unparalleled data-crunching capabilities an order of magnitude faster compared to other solutions written in higher level or even interpreted languages which are inefficient at processing large amounts of data.
  • 14
    PandaAI

    PandaAI

    PandaAI

    ​PandaAI is an AI-driven platform that transforms natural language queries into actionable data insights, streamlining the data analysis process. It allows users to connect databases effortlessly, enabling instant report generation through agentic AI and text-to-SQL layers. Users can interact with their data using conversational AI, facilitating intuitive, human-like queries. It also supports team collaboration by allowing users to save responses as data snippets and share them with colleagues. To get started, users can install the pandasai Python library, set up their API key, load their datasets, and push them to the platform for analysis.
    Starting Price: €20 per month
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    Multimodal

    Multimodal

    Multimodal

    Multimodal builds and manages secure, integrated, and tailored AI automation for complex workflows in financial services. Our enterprise-grade AI agents are trained on company data for greater precision and work together as your digital workforce. Our AI Agents process documents, query databases, power chatbots, make decisions, and generate reports. They automate end-to-end workflows and self-learn to improve over time. Unstructured AI is an Extract, Transform, Load (ETL) layer to process complex, unstructured documents for RAG or AI applications. Document AI is trained on your schema to extract, label, and organize data from loan applications, claims, PDF reports, and more. Conversational AI serves as your in-house chatbot that accesses unstructured internal data to provide customer and employee support. Database AI accesses company databases to answer queries, interpret datasets, and provide actionable insights.
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    MongoDB Compass
    Easily work with your data in Compass, the GUI built by — and for — MongoDB. Compass provides everything from schema analysis to index optimization to aggregation pipelines in a single, centralized interface. Dissect your document schema to understand your data at a deeper level. Compass samples and analyzes your documents to provide detailed metadata on your collections, including the ranges of dates and integers, most frequent values, and more. Find the data you need in seconds with Compass’ built-in query bar. Filter the documents within your collection using intuitive query operators that correspond to expressions in other languages. Sample, sort, and modify results with high granularity. Add new indexes and remove underperforming ones to optimize queries, monitor real-time server and database metrics, investigate performance issues with the visual explain plan, and more.
    Starting Price: Free
  • 17
    Increment

    Increment

    Increment

    Using our insights and recommendation suite, controlling and optimizing costs becomes a walk in the park. Our models calculate cost to the lowest granularity. Understand what a single query costs, or a table. Aggregate data workloads to understand their collective cost over time. Understand which actions will yield which results. Keep your team focused and tackle only the tech debt worth tackling. Understand how to configure your data workloads in a cost-optimal way. Drive efficient savings without having to re-write queries or drop tables. Educate your team members through query recommendations. Balance effort and impact and ensure your work has an optimal ROI. Teams save up to 30% of their costs with increments.
  • 18
    Kibana

    Kibana

    Elastic

    Kibana is a free and open user interface that lets you visualize your Elasticsearch data and navigate the Elastic Stack. Do anything from tracking query load to understanding the way requests flow through your apps. Kibana gives you the freedom to select the way you give shape to your data. With its interactive visualizations, start with one question and see where it leads you. Kibana core ships with the classics: histograms, line graphs, pie charts, sunbursts, and more. And, of course, you can search across all of your documents. Leverage Elastic Maps to explore location data, or get creative and visualize custom layers and vector shapes. Perform advanced time series analysis on your Elasticsearch data with our curated time series UIs. Describe queries, transformations, and visualizations with powerful, easy-to-learn expressions.
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    HStreamDB
    A streaming database is purpose-built to ingest, store, process, and analyze massive data streams. It is a modern data infrastructure that unifies messaging, stream processing, and storage to help get value out of your data in real-time. Ingest massive amounts of data continuously generated from various sources, such as IoT device sensors. Store millions of data streams reliably in a specially designed distributed streaming data storage cluster. Consume data streams in real-time as fast as from Kafka by subscribing to topics in HStreamDB. With the permanent data stream storage, you can playback and consume data streams anytime. Process data streams based on event-time with the same familiar SQL syntax you use to query data in a relational database. You can use SQL to filter, transform, aggregate, and even join multiple data streams.
    Starting Price: Free
  • 20
    PipelineDB

    PipelineDB

    PipelineDB

    PipelineDB is a PostgreSQL extension for high-performance time-series aggregation, designed to power realtime reporting and analytics applications. PipelineDB allows you to define continuous SQL queries that perpetually aggregate time-series data and store only the aggregate output in regular, queryable tables. You can think of this concept as extremely high-throughput, incrementally updated materialized views that never need to be manually refreshed. Raw time-series data is never written to disk, making PipelineDB extremely efficient for aggregation workloads. Continuous queries produce their own output streams, and thus can be chained together into arbitrary networks of continuous SQL.
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    Apache Ignite

    Apache Ignite

    Apache Ignite

    Use Ignite as a traditional SQL database by leveraging JDBC drivers, ODBC drivers, or the native SQL APIs that are available for Java, C#, C++, Python, and other programming languages. Seamlessly join, group, aggregate, and order your distributed in-memory and on-disk data. Accelerate your existing applications by 100x using Ignite as an in-memory cache or in-memory data grid that is deployed over one or more external databases. Think of a cache that you can query with SQL, transact, and compute on. Build modern applications that support transactional and analytical workloads by using Ignite as a database that scales beyond the available memory capacity. Ignite allocates memory for your hot data and goes to disk whenever applications query cold records. Execute kilobyte-size custom code over petabytes of data. Turn your Ignite database into a distributed supercomputer for low-latency calculations, complex analytics, and machine learning.
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    Apache DataFusion

    Apache DataFusion

    Apache Software Foundation

    Apache DataFusion is an extensible, high-performance query engine written in Rust that utilizes Apache Arrow as its in-memory format. Designed for developers building data-centric systems such as databases, data frames, machine learning, and streaming applications, DataFusion offers SQL and DataFrame APIs, a vectorized, multi-threaded, streaming execution engine, and support for partitioned data sources. It natively supports formats like CSV, Parquet, JSON, and Avro, and allows for seamless integration with object stores including AWS S3, Azure Blob Storage, and Google Cloud Storage. The engine features a comprehensive query planner, a state-of-the-art optimizer with capabilities like expression coercion and simplification, projection and filter pushdown, sort and distribution-aware optimizations, and automatic join reordering. DataFusion is highly customizable, enabling the addition of user-defined scalar, aggregate, and window functions, custom data sources, query languages, etc.
    Starting Price: Free
  • 23
    Studio 3T

    Studio 3T

    Studio 3T

    Auto-complete queries in a built-in mongo shell that highlights syntax errors as you type and saves your query history. Perfect for MongoDB beginners, a time-saver for pros. Use a drag-and-drop UI to build complex find() queries and filter array elements. Break down aggregation queries into manageable steps and build them stage by stage, for easier debugging and querying. Generate instant code in JavaScript (Node.js), Java (2.x and 3.x driver API), Python, C#, PHP, and Ruby from MongoDB and SQL queries that you can copy and paste into your application. Save MongoDB imports, exports, data comparisons, and migrations as tasks that you can run on demand. Or even better, skip the reminders and schedule them to run exactly when you need them. Make changes to your collection’s schema in just a few clicks, perfect for schema performance tuning, restructuring, or cleaning up after data migration.
    Starting Price: $499/year/user
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    NeoBase

    NeoBase

    NeoBase

    ​NeoBase is an AI-powered database assistant that enables users to query, analyze, and manage databases using natural language. It supports multiple databases. Users can connect their databases and interact with them through a chat interface, allowing for efficient management of transactions and performance optimization. NeoBase is self-hosted and open source, providing users with control over their data. NeoBase features a sleek Neo Brutalism design, making database visualization intuitive and efficient. With NeoBase, users can transform natural language into optimized queries, simplifying complex database operations. ​NeoBase manages your database schema for you while giving you the flexibility to control it. Execute queries, rollback if needed, and visualize large volumes of data with ease. Get AI-driven suggestions to improve database performance.
    Starting Price: Free
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    SelectDB

    SelectDB

    SelectDB

    SelectDB is a modern data warehouse based on Apache Doris, which supports rapid query analysis on large-scale real-time data. From Clickhouse to Apache Doris, to achieve the separation of the lake warehouse and upgrade to the lake warehouse. The fast-hand OLAP system carries nearly 1 billion query requests every day to provide data services for multiple scenes. Due to the problems of storage redundancy, resource seizure, complicated governance, and difficulty in querying and adjustment, the original lake warehouse separation architecture was decided to introduce Apache Doris lake warehouse, combined with Doris's materialized view rewriting ability and automated services, to achieve high-performance data query and flexible data governance. Write real-time data in seconds, and synchronize flow data from databases and data streams. Data storage engine for real-time update, real-time addition, and real-time pre-polymerization.
    Starting Price: $0.22 per hour
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    SigNoz

    SigNoz

    SigNoz

    SigNoz is an open source Datadog or New Relic alternative. A single tool for all your observability needs, APM, logs, metrics, exceptions, alerts, and dashboards powered by a powerful query builder. You don’t need to manage multiple tools for traces, metrics, and logs. Get great out-of-the-box charts and a powerful query builder to dig deeper into your data. Using an open source standard frees you from vendor lock-in. Use auto-instrumentation libraries of OpenTelemetry to get started with little to no code change. OpenTelemetry is a one-stop solution for all your telemetry needs. A single standard for all telemetry signals means increased developer productivity and consistency across teams. Write queries on all telemetry signals. Run aggregates, and apply filters and formulas to get deeper insights from your data. SigNoz uses ClickHouse, a fast open source distributed columnar database. Ingestion and aggregations are lightning-fast.
    Starting Price: $199 per month
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    AI Query

    AI Query

    AI Query

    Use simple English and let AI do the heavy lifting for you. With AI Query anyone can create efficient SQL queries, without even knowing a thing about it. Once your database schema is ready, you can easily generate SQL queries with simple text prompts. Let the AI do the work for you.
    Starting Price: $10 per month
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    Hydrolix

    Hydrolix

    Hydrolix

    Hydrolix is a streaming data lake that combines decoupled storage, indexed search, and stream processing to deliver real-time query performance at terabyte-scale for a radically lower cost. CFOs love the 4x reduction in data retention costs. Product teams love 4x more data to work with. Spin up resources when you need them and scale to zero when you don’t. Fine-tune resource consumption and performance by workload to control costs. Imagine what you can build when you don’t have to sacrifice data because of budget. Ingest, enrich, and transform log data from multiple sources including Kafka, Kinesis, and HTTP. Return just the data you need, no matter how big your data is. Reduce latency and costs, eliminate timeouts, and brute force queries. Storage is decoupled from ingest and query, allowing each to independently scale to meet performance and budget targets. Hydrolix’s high-density compression (HDX) typically reduces 1TB of stored data to 55GB.
    Starting Price: $2,237 per month
  • 29
    Alibaba Cloud TSDB
    Time Series Database (TSDB) supports high-speed data reading and writing. It offers high compression ratios for cost-efficient data storage. This service also supports visualization of precision reduction, interpolation, multi-metric aggregate computing, and query results. The TSDB service reduces storage costs and improves the efficiency of data writing, query, and analysis. This enables you to handle large amounts of data points and collect data more frequently. This service has been widely applied to systems in different industries, such as IoT monitoring systems, enterprise energy management systems (EMSs), production security monitoring systems, and power supply monitoring systems. Optimizes database architectures and algorithms. TSDB can read or write millions of data points within seconds. Applies an efficient compression algorithm to reduce the size of each data point to 2 bytes, saving more than 90% in storage costs.
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    Apache Druid
    Apache Druid is an open source distributed data store. Druid’s core design combines ideas from data warehouses, timeseries databases, and search systems to create a high performance real-time analytics database for a broad range of use cases. Druid merges key characteristics of each of the 3 systems into its ingestion layer, storage format, querying layer, and core architecture. Druid stores and compresses each column individually, and only needs to read the ones needed for a particular query, which supports fast scans, rankings, and groupBys. Druid creates inverted indexes for string values for fast search and filter. Out-of-the-box connectors for Apache Kafka, HDFS, AWS S3, stream processors, and more. Druid intelligently partitions data based on time and time-based queries are significantly faster than traditional databases. Scale up or down by just adding or removing servers, and Druid automatically rebalances. Fault-tolerant architecture routes around server failures.
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    Metacode

    Metacode

    Metacode

    Intelligent visual designer to build UI, data layer and workflows of your application. Outputs elegant source code written using React and NodeJS. Stick with the framework and language that works for you. Your designed application is generated using a widely adopted architecture with React, Redux and React-router for the frontend and NodeJS + Express for the backend. Once you have your application view designed, it's easy to populate all your components with real data by binding them to the database using a visual SQL query builder. The queried data is immediately reflected in the components. Create complex business application user interfaces by dragging and dropping components. It's as easy as using a mockup tool. Also, our designer is smart enough to transform your designs to a beautiful bootstrap theme. We automate a lot of repetitive tasks, so you get to focus on the things that matter.
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    Aircloak Insights
    Aircloak Insights is a transparent proxy sitting between analysts and the sensitive data they need to work with. Analysts query the system like normal, using SQL or dashboards like Tableau. Aircloak Insights intercepts the query and tailors it to the data backend which may be SQL or a NoSQL big data store. Results are returned via the proxy which ensures they are aggregated and fully anonymized. Aircloak Insights integrates directly in your existing workflow. You can query your sensitive datasets using the query editor in our easy-to-use web interface, Insights Air, or connect using business intelligence tools like Tableau or any other tools or dashboards that know how to communicate using the Postgres Message Protocol. Aircloak Insights also allows you to run queries programmatically using a RESTful API.
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    PuppyGraph

    PuppyGraph

    PuppyGraph

    PuppyGraph empowers you to seamlessly query one or multiple data stores as a unified graph model. Graph databases are expensive, take months to set up, and need a dedicated team. Traditional graph databases can take hours to run multi-hop queries and struggle beyond 100GB of data. A separate graph database complicates your architecture with brittle ETLs and inflates your total cost of ownership (TCO). Connect to any data source anywhere. Cross-cloud and cross-region graph analytics. No complex ETLs or data replication is required. PuppyGraph enables you to query your data as a graph by directly connecting to your data warehouses and lakes. This eliminates the need to build and maintain time-consuming ETL pipelines needed with a traditional graph database setup. No more waiting for data and failed ETL processes. PuppyGraph eradicates graph scalability issues by separating computation and storage.
    Starting Price: Free
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    Grafbase

    Grafbase

    Grafbase

    Grafbase is a high-performance GraphQL platform designed to help developers build, unify, and manage APIs by combining multiple data sources into a single federated API layer. It acts as a GraphQL federation gateway that aggregates services such as databases, microservices, REST APIs, and third-party systems into one unified endpoint that applications can query efficiently. Developers can compose a federated graph from multiple independent subgraphs, allowing different teams or services to evolve independently while still presenting a single coherent API to clients. Grafbase includes a schema registry and governance tools that enable teams to manage schema changes, run checks to detect breaking changes, and collaborate on schema proposals before deployment. It also provides analytics, observability, and performance monitoring features that track API usage and help teams optimize their data infrastructure.
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    Advanced ETL Processor

    Advanced ETL Processor

    DB Software Laboratory

    Advanced ETL Processor is a professional ETL and data integration solution designed for developers, data engineers, and IT teams who need to automate data workflows across multiple systems. The software supports a wide range of data sources and formats, including Excel, CSV, XML, JSON, QVD/QVX, REST APIs, and major databases such as MySQL, PostgreSQL, SQL Server, Oracle, and MariaDB. Users can build visual ETL workflows to extract, transform, validate, and load data with advanced mapping, filtering, aggregation, and scripting capabilities. Advanced ETL Processor is commonly used for data migration, system integration, reporting, and business intelligence. Its automation and scheduling features help reduce manual work, improve data quality, and ensure reliable data synchronization between systems. The platform is suitable for both simple data transfers and complex enterprise-level ETL processes, without requiring heavy custom coding.
    Starting Price: $690 per user per year
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    Grafana Loki
    Grafana Loki is an open source log aggregation system designed to efficiently collect, store, and query logs from various sources. Unlike traditional logging systems, Loki is optimized for cloud-native applications, making it a great fit for modern, containerized environments like Kubernetes. It works seamlessly with Grafana for visualizing log data alongside metrics and traces, providing a unified observability platform. Loki indexes only metadata, such as labels and timestamps, which reduces the amount of data stored and improves query performance compared to more traditional log management systems. This lightweight approach allows for easier scalability and cost-effective storage. Loki also supports log aggregation from various sources, including Syslog, application logs, and container logs, and integrates with other observability tools to provide a complete view of system performance.
    Starting Price: Free
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    WatermelonDB

    WatermelonDB

    WatermelonDB

    ​WatermelonDB is a reactive database framework designed to build powerful React and React Native apps that scale from hundreds to tens of thousands of records while remaining fast. It ensures instant app launch regardless of data volume, supports lazy loading to load data only when needed, and offers offline-first capabilities with synchronization to your own backend. It is multiplatform. Optimized for React, it allows easy integration of data into components and is framework-agnostic, enabling the use of its JavaScript API with other UI frameworks. Built on a robust SQLite foundation, WatermelonDB provides static typing with Flow or TypeScript and optional reactivity through an RxJS API. WatermelonDB addresses performance issues in complex applications by loading nothing until requested and performing all querying directly on SQLite on a separate native thread, ensuring most queries resolve instantly.
    Starting Price: Free
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    Axibase Time Series Database
    Parallel query engine with time- and symbol-indexed data access. Extended SQL syntax with advanced filtering and aggregations. Consolidate quotes, trades, snapshots, and reference data in one place. Strategy backtesting on high-frequency data. Quantitative and market microstructure research. Granular transaction cost analysis and rollup reporting. Market surveillance and anomaly detection. Non-transparent ETF/ETN decomposition. FAST, SBE, and proprietary protocols. Plain text protocol. Consolidated and direct feeds. Built-in latency monitoring tools. End-of-day archives. ETL from institutional and retail financial data platforms. Parallel SQL engine with syntax extensions. Advanced filtering by trading session, auction stage, index composition. Optimized aggregates for OHLCV and VWAP calculations. Interactive SQL console with auto-completion. API endpoint for programmatic integration. Scheduled SQL reporting with email, file, and web delivery. JDBC and ODBC drivers.
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    Layerup

    Layerup

    Layerup

    Extract and Transform any data from any data source with Natural Language connect to your data source - everything ranging from your DB to your CRM to your billing solution. Improve Productivity by 5-10x Forget about wasting time on clunky BI tools. Use Natural Language to query any complex data in seconds. Transition from DIY tools to non-DIY AI-powered tools. Generate complex dashboards and reports in a few lines. No more SQL or complex formulas - let Layerup AI do the heavy lifting for you. Layerup not only gives you instant answer to questions that would require 5-40 hours/month on SQL queries, but it will act as your personal data analyst 24/7 while providing you complex dashboards/charts that you can embed anywhere.
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    Querona

    Querona

    YouNeedIT

    We make BI & Big Data analytics work easier and faster. Our goal is to empower business users and make always-busy business and heavily loaded BI specialists less dependent on each other when solving data-driven business problems. If you have ever experienced a lack of data you needed, time to consuming report generation or long queue to your BI expert, consider Querona. Querona uses a built-in Big Data engine to handle growing data volumes. Repeatable queries can be cached or calculated in advance. Optimization needs less effort as Querona automatically suggests query improvements. Querona empowers business analysts and data scientists by putting self-service in their hands. They can easily discover and prototype data models, add new data sources, experiment with query optimization and dig in raw data. Less IT is needed. Now users can get live data no matter where it is stored. If databases are too busy to be queried live, Querona will cache the data.
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    QueryTree

    QueryTree

    D4 Software

    QueryTree makes it easy to build and share reports on your software's databases. QueryTree is an open-source ad hoc reporting and visualization solution for your app. Download from Github, run it from Source, Binaries or using Docker, then connect it to any Microsoft SQL Server, MySQL or PostgreSQL database, and you’re good to go. As your app’s missing report screen, QueryTree enables technical and non-technical users alike can easily select, filter, group, aggregate and visualize data from any table in any database. Users can export their results, share reports with their team, and set up schedule emails to keep everyone updated. Give your users our intuitive and user-friendly report builder to explore, select, and summarize their data. Generate useful interactive charts that visually summarize what's really going on without writing a single line of code. Securely connect your MySQL, PostgreSQL, or Microsoft SQL Server database in just a few minutes.
    Starting Price: $29 per month
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    Espresso AI

    Espresso AI

    Espresso AI

    Espresso AI is a data-warehouse optimization system built to reduce the compute and query costs of platforms like Snowflake and Databricks SQL by deploying machine-learning agents that manage scaling, scheduling, and query rewriting in real time. It layers three core agents; an autoscaling agent that predicts workload spikes and minimizes idle compute, a scheduling agent that routes queries dynamically across clusters to maximize utilization and significantly reduce idle time, and a query agent that rewrites SQL using large language models combined with formal verification to ensure equivalent results while improving efficiency. It offers fast deployment (minutes rather than months) and a pricing model tied to savings, so that if it does not reduce your bill, you don’t pay. By automating hundreds of thousands of optimization decisions per day, Espresso AI provides dramatic cost reductions while enabling engineering teams to focus on value-add features.
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    Oracle Autonomous Data Warehouse
    Oracle Autonomous Data Warehouse is a cloud data warehouse service that eliminates all the complexities of operating a data warehouse, dw cloud, data warehouse center, securing data, and developing data-driven applications. It automates provisioning, configuring, securing, tuning, scaling, and backing up of the data warehouse. It includes tools for self-service data loading, data transformations, business models, automatic insights, and built-in converged database capabilities that enable simpler queries across multiple data types and machine learning analysis. It’s available in both the Oracle public cloud and customers' data centers with Oracle Cloud@Customer. Detailed analysis by industry expert DSC illustrates why Oracle Autonomous Data Warehouse is a better pick for the majority of global organizations. Learn about applications and tools that are compatible with Autonomous Data Warehouse.
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    Polygon.io

    Polygon.io

    Polygon.io

    See each and every Trade & Quote happening in the US in real time, and access trillions of rows of historical tick data in an instant using our APIs. There is no limit to how much you can use our stock data APIs. No maximum queries per minute or daily call limits on all premium plans. Our market data platform provides low latency real-time data with a mean latency of 20ms, orders of magnitude faster than competitors. See the entire market at a glance with our powerful Snapshot APIs. You can also query the gainers and losers for the current day. 1min - 1yr aggregate intervals. Use our aggregates APIs to query any timespan, 1 min, 7 min, 16 day? Anything is possible. Get stocks data directly from the source, and know exactly what you're going to pay. Don't waste time and money on sales or middlemen.
    Starting Price: $99 per month
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    WinSQL

    WinSQL

    Synametrics Technologies

    WinSQL is a powerful universal database management tool that is used by 90 percent of Fortune 500 companies and more than a million programmers and DBAs around the globe. WinSQL is a generic querying tool that connects to any relational database (RDBMS) for which an Open Database Connectivity (ODBC) driver is available, virtually all RDBMS on the market today. Connect to a variety of databases, including: heavy duty vendors Oracle, MS SQL Server, DB2, Sybase, Informix to lightweight backends like MS Access, DBase, and Text File. Generate royalty-free executables that can be used by your business users to run queries. These can be either static or dynamic queries that pull fresh data from the back-end. Export or simply open any query results into MS Excel with just a click of your mouse. You can even import an existing Excel spreadsheet to a database table by simply dragging an *.XSL file in the catalog tree.
    Starting Price: $99.00/year/user
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    Yandex Managed Service for YDB
    Serverless computing is ideal for systems with unpredictable loads. Storage scaling, query execution, and backup layers are fully automated. The compatibility of the service API in serverless mode allows you to use the AWS SDKs for Java, JavaScript, Node.js, .NET, PHP, Python, and Ruby. YDB is hosted in three availability zones, ensuring availability even if a node or availability zone goes offline. If equipment or a data center fails, the system automatically recovers and continues working. YDB is tailored to meet high-performance requirements and can process hundreds of thousands of transactions per second with low latency. The system was designed to handle hundreds of petabytes of data.
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    Clinical Insights Manager

    Clinical Insights Manager

    Capsule Technologies

    Clinical Insights Manager is a cloud-based, enterprise-wide platform designed to capture, store, and analyze high-fidelity retrospective patient data from both Philips and third-party medical devices, enabling healthcare organizations to transform large volumes of clinical data into actionable insights. Built on an open and scalable architecture, it aggregates and filters high-resolution data, including diagnostic-quality ECG, and presents it through intuitive dashboards that allow users to easily navigate, query, and analyze complex datasets. It supports quality improvement, alarm management, research initiatives, and operational efficiency by ensuring data integrity and providing comprehensive access to historical patient information such as waveforms, numerics, and alarm events. It includes applications like Alarm Insights Manager, Data Viewer, and Telemetry Insights Manager, which provide tools for evaluating alarm performance.
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    TimescaleDB

    TimescaleDB

    Tiger Data

    TimescaleDB is the leading time-series database built on PostgreSQL, designed to handle massive volumes of real-time data efficiently. It enables organizations to store, analyze, and query time-series data — such as IoT sensor data, financial transactions, or event logs — using standard SQL. With hypertables, TimescaleDB automatically partitions data by time and ID for fast ingestion and predictable query performance. Its compression engine reduces storage costs by up to 95%, while continuous aggregates make real-time dashboards instantly responsive. Fully compatible with PostgreSQL, it integrates seamlessly with existing tools and applications. TimescaleDB combines the simplicity of Postgres with the scalability and speed of a specialized analytical system.
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    TaffyDB

    TaffyDB

    TaffyDB

    ​TaffyDB is an open source JavaScript library that brings powerful database functionality into your JavaScript applications. It offers a small file size with extremely fast queries and a powerful JavaScript-centric data selection engine. TaffyDB includes database-inspired features such as count, update, and insert, and provides robust cross-browser support. It is easily extended with your own functions and is compatible with any DOM library, as well as server-side JavaScript. Creating a database is straightforward, you can create a new empty database, a database with a single object, an array, or a JSON string. Once you have a database, you can run queries against it by calling the root function and building filter objects. TaffyDB allows you to filter using the database name and object comparison, access data easily, and modify data on the fly. You can also use functions to give you full control over the results of your query.
    Starting Price: Free
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    Apache Pinot

    Apache Pinot

    Apache Corporation

    Pinot is designed to answer OLAP queries with low latency on immutable data. Pluggable indexing technologies - Sorted Index, Bitmap Index, Inverted Index. Joins are currently not supported, but this problem can be overcome by using Trino or PrestoDB for querying. SQL like language that supports selection, aggregation, filtering, group by, order by, distinct queries on data. Consist of of both offline and real-time table. Use real-time table only to cover segments for which offline data may not be available yet. Detect the right anomalies by customizing anomaly detect flow and notification flow.