Alternatives to Dremio
Compare Dremio alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Dremio in 2026. Compare features, ratings, user reviews, pricing, and more from Dremio competitors and alternatives in order to make an informed decision for your business.
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1
Teradata VantageCloud
Teradata
Teradata VantageCloud: The complete cloud analytics and data platform for AI. Teradata VantageCloud is an enterprise-grade, cloud-native data and analytics platform that unifies data management, advanced analytics, and AI/ML capabilities in a single environment. Designed for scalability and flexibility, VantageCloud supports multi-cloud and hybrid deployments, enabling organizations to manage structured and semi-structured data across AWS, Azure, Google Cloud, and on-premises systems. It offers full ANSI SQL support, integrates with open-source tools like Python and R, and provides built-in governance for secure, trusted AI. VantageCloud empowers users to run complex queries, build data pipelines, and operationalize machine learning models—all while maintaining interoperability with modern data ecosystems. -
2
Google Cloud BigQuery
Google
BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven. Gemini in BigQuery offers AI-driven tools for assistance and collaboration, such as code suggestions, visual data preparation, and smart recommendations designed to boost efficiency and reduce costs. BigQuery delivers an integrated platform featuring SQL, a notebook, and a natural language-based canvas interface, catering to data professionals with varying coding expertise. This unified workspace streamlines the entire analytics process. -
3
dbt
dbt Labs
dbt helps data teams transform raw data into trusted, analysis-ready datasets faster. With dbt, data analysts and data engineers can collaborate on version-controlled SQL models, enforce testing and documentation standards, lean on detailed metadata to troubleshoot and optimize pipelines, and deploy transformations reliably at scale. Built on modern software engineering best practices, dbt brings transparency and governance to every step of the data transformation workflow. Thousands of companies, from startups to Fortune 500 enterprises, rely on dbt to improve data quality and trust as well as drive efficiencies and reduce costs as they deliver AI-ready data across their organization. Whether you’re scaling data operations or just getting started, dbt empowers your team to move from raw data to actionable analytics with confidence. -
4
AnalyticsCreator
AnalyticsCreator
AnalyticsCreator is a metadata-driven data warehouse automation application for teams working in the Microsoft data ecosystem. It enables data engineers to design, generate, and maintain production-ready data products across Microsoft SQL Server, Azure Data Factory, and Microsoft Fabric. By using centralized metadata, AnalyticsCreator generates ELT pipelines, dimensional models, historization logic, and analytical models in a consistent, version-controlled way. This reduces manual implementation effort and tool sprawl while ensuring transparency through built-in lineage tracking and clear visibility into data dependencies and change impact. With CI/CD integration via Azure DevOps and GitHub, plus support for custom SQL, AnalyticsCreator helps data teams scale delivery, enforce standards, and maintain control as complexity grows. -
5
Snowflake
Snowflake
Snowflake is a comprehensive AI Data Cloud platform designed to eliminate data silos and simplify data architectures, enabling organizations to get more value from their data. The platform offers interoperable storage that provides near-infinite scale and access to diverse data sources, both inside and outside Snowflake. Its elastic compute engine delivers high performance for any number of users, workloads, and data volumes with seamless scalability. Snowflake’s Cortex AI accelerates enterprise AI by providing secure access to leading large language models (LLMs) and data chat services. The platform’s cloud services automate complex resource management, ensuring reliability and cost efficiency. Trusted by over 11,000 global customers across industries, Snowflake helps businesses collaborate on data, build data applications, and maintain a competitive edge.Starting Price: $2 compute/month -
6
Paxata
Paxata
Paxata is a visually-dynamic, intuitive solution that enables business analysts to rapidly ingest, profile, and curate multiple raw datasets into consumable information in a self-service manner, greatly accelerating development of actionable business insights. In addition to empowering business analysts and SMEs, Paxata also provides a rich set of workload automation and embeddable data preparation capabilities to operationalize and deliver data preparation as a service within other applications. The Paxata Adaptive Information Platform (AIP) unifies data integration, data quality, semantic enrichment, re-use & collaboration, and also provides comprehensive data governance and audit capabilities with self-documenting data lineage. The Paxata AIP utilizes a native multi-tenant elastic cloud architecture and is the only modern information platform that is currently deployed as a multi-cloud hybrid information fabric. -
7
Qubole
Qubole
Qubole is a simple, open, and secure Data Lake Platform for machine learning, streaming, and ad-hoc analytics. Our platform provides end-to-end services that reduce the time and effort required to run Data pipelines, Streaming Analytics, and Machine Learning workloads on any cloud. No other platform offers the openness and data workload flexibility of Qubole while lowering cloud data lake costs by over 50 percent. Qubole delivers faster access to petabytes of secure, reliable and trusted datasets of structured and unstructured data for Analytics and Machine Learning. Users conduct ETL, analytics, and AI/ML workloads efficiently in end-to-end fashion across best-of-breed open source engines, multiple formats, libraries, and languages adapted to data volume, variety, SLAs and organizational policies. -
8
Tabular
Tabular
Tabular is an open table store from the creators of Apache Iceberg. Connect multiple computing engines and frameworks. Decrease query time and storage costs by up to 50%. Centralize enforcement of data access (RBAC) policies. Connect any query engine or framework, including Athena, BigQuery, Redshift, Snowflake, Databricks, Trino, Spark, and Python. Smart compaction, clustering, and other automated data services reduce storage costs and query times by up to 50%. Unify data access at the database or table. RBAC controls are simple to manage, consistently enforced, and easy to audit. Centralize your security down to the table. Tabular is easy to use plus it features high-powered ingestion, performance, and RBAC under the hood. Tabular gives you the flexibility to work with multiple “best of breed” compute engines based on their strengths. Assign privileges at the data warehouse database, table, or column level.Starting Price: $100 per month -
9
Starburst Enterprise
Starburst Data
Starburst helps you make better decisions with fast access to all your data; Without the complexity of data movement and copies. Your company has more data than ever before, but your data teams are stuck waiting to analyze it. Starburst unlocks access to data where it lives, no data movement required, giving your teams fast & accurate access to more data for analysis. Starburst Enterprise is a fully supported, production-tested and enterprise-grade distribution of open source Trino (formerly Presto® SQL). It improves performance and security while making it easy to deploy, connect, and manage your Trino environment. Through connecting to any source of data – whether it’s located on-premise, in the cloud, or across a hybrid cloud environment – Starburst lets your team use the analytics tools they already know & love while accessing data that lives anywhere. -
10
Trino
Trino
Trino is a query engine that runs at ludicrous speed. Fast-distributed SQL query engine for big data analytics that helps you explore your data universe. Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low-latency analytics. The largest organizations in the world use Trino to query exabyte-scale data lakes and massive data warehouses alike. Supports diverse use cases, ad-hoc analytics at interactive speeds, massive multi-hour batch queries, and high-volume apps that perform sub-second queries. Trino is an ANSI SQL-compliant query engine, that works with BI tools such as R, Tableau, Power BI, Superset, and many others. You can natively query data in Hadoop, S3, Cassandra, MySQL, and many others, without the need for complex, slow, and error-prone processes for copying the data. Access data from multiple systems within a single query.Starting Price: Free -
11
AtScale
AtScale
AtScale helps accelerate and simplify business intelligence resulting in faster time-to-insight, better business decisions, and more ROI on your Cloud analytics investment. Eliminate repetitive data engineering tasks like curating, maintaining and delivering data for analysis. Define business definitions in one location to ensure consistent KPI reporting across BI tools. Accelerate time to insight from data while efficiently managing cloud compute costs. Leverage existing data security policies for data analytics no matter where data resides. AtScale’s Insights workbooks and models let you perform Cloud OLAP multidimensional analysis on data sets from multiple providers – with no data prep or data engineering required. We provide built-in easy to use dimensions and measures to help you quickly derive insights that you can use for business decisions. -
12
IOMETE
IOMETE
IOMETE is a self-hosted data lakehouse platform built on Apache Iceberg, Apache Spark, and Kubernetes. Run it on-premises or in your private cloud — your infrastructure, your data, your control. Built for enterprises in regulated industries, IOMETE eliminates third-party ICT risk at the data layer by architecture — not by contract. No SaaS dependencies. No data leaving your perimeter. Compliance with GDPR, DORA, and NIS2 is structural, not contractual. Included in one platform: - Data Lakehouse(s) - Data Catalog - SQL Editor - Apache Spark Jobs - ML Notebooks - Orchestration Engine - Spark Connect Key capabilities: Apache Iceberg-native storage, Kubernetes-native deployment (K8s + OpenShift), row/column/tag-based access control, Data Mesh support, air-gapped and zero-trust compatible. Transparent pricing — CPU-based, no per-query fees, no billing surprises.Starting Price: Free -
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Apache Drill
The Apache Software Foundation
Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage -
14
Apache Druid
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. -
15
Denodo
Denodo Technologies
The core technology to enable modern data integration and data management solutions. Quickly connect disparate structured and unstructured sources. Catalog your entire data ecosystem. Data stays in the sources and it is accessed on demand, with no need to create another copy. Build data models that suit the needs of the consumer, even across multiple sources. Hide the complexity of your back-end technologies from the end users. The virtual model can be secured and consumed using standard SQL and other formats like REST, SOAP and OData. Easy access to all types of data. Full data integration and data modeling capabilities. Active Data Catalog and self-service capabilities for data & metadata discovery and data preparation. Full data security and data governance capabilities. Fast intelligent execution of data queries. Real-time data delivery in any format. Ability to create data marketplaces. Decoupling of business applications from data systems to facilitate data-driven strategies. -
16
Delta Lake
Delta Lake
Delta Lake is an open-source storage layer that brings ACID transactions to Apache Spark™ and big data workloads. Data lakes typically have multiple data pipelines reading and writing data concurrently, and data engineers have to go through a tedious process to ensure data integrity, due to the lack of transactions. Delta Lake brings ACID transactions to your data lakes. It provides serializability, the strongest level of isolation level. Learn more at Diving into Delta Lake: Unpacking the Transaction Log. In big data, even the metadata itself can be "big data". Delta Lake treats metadata just like data, leveraging Spark's distributed processing power to handle all its metadata. As a result, Delta Lake can handle petabyte-scale tables with billions of partitions and files at ease. Delta Lake provides snapshots of data enabling developers to access and revert to earlier versions of data for audits, rollbacks or to reproduce experiments. -
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Databricks Data Intelligence Platform
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
18
Varada
Varada
Varada’s dynamic and adaptive big data indexing solution enables to balance performance and cost with zero data-ops. Varada’s unique big data indexing technology serves as a smart acceleration layer on your data lake, which remains the single source of truth, and runs in the customer cloud environment (VPC). Varada enables data teams to democratize data by operationalizing the entire data lake while ensuring interactive performance, without the need to move data, model or manually optimize. Our secret sauce is our ability to automatically and dynamically index relevant data, at the structure and granularity of the source. Varada enables any query to meet continuously evolving performance and concurrency requirements for users and analytics API calls, while keeping costs predictable and under control. The platform seamlessly chooses which queries to accelerate and which data to index. Varada elastically adjusts the cluster to meet demand and optimize cost and performance. -
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Stardog
Stardog Union
With ready access to the richest flexible semantic layer, explainable AI, and reusable data modeling, data engineers and scientists can be 95% more productive — create and expand semantic data models, understand any data interrelationship, and run federated queries to speed time to insight. Stardog offers the most advanced graph data virtualization and high-performance graph database — up to 57x better price/performance — to connect any data lakehouse, warehouse or enterprise data source without moving or copying data. Scale use cases and users at lower infrastructure cost. Stardog’s inference engine intelligently applies expert knowledge dynamically at query time to uncover hidden patterns or unexpected insights in relationships that enable better data-informed decisions and business outcomes.Starting Price: $0 -
20
Mozart Data
Mozart Data
Mozart Data is the all-in-one modern data platform that makes it easy to consolidate, organize, and analyze data. Start making data-driven decisions by setting up a modern data stack in an hour - no engineering required. -
21
Archon Data Store
Platform 3 Solutions
Archon Data Store is a next-generation enterprise data archiving platform designed to help organizations manage rapid data growth, reduce legacy application costs, and meet global compliance standards. Built on a modern Lakehouse architecture, Archon Data Store unifies data lakes and data warehouses to deliver secure, scalable, and analytics-ready archival storage. The platform supports on-premise, cloud, and hybrid deployments with AES-256 encryption, audit trails, metadata governance, and role-based access control. Archon Data Store offers intelligent storage tiering, high-performance querying, and seamless integration with BI tools. It enables efficient application decommissioning, cloud migration, and digital modernization while transforming archived data into a strategic asset. With Archon Data Store, organizations can ensure long-term compliance, optimize storage costs, and unlock AI-driven insights from historical data. -
22
Lyftrondata
Lyftrondata
Whether you want to build a governed delta lake, data warehouse, or simply want to migrate from your traditional database to a modern cloud data warehouse, do it all with Lyftrondata. Simply create and manage all of your data workloads on one platform by automatically building your pipeline and warehouse. Analyze it instantly with ANSI SQL, BI/ML tools, and share it without worrying about writing any custom code. Boost the productivity of your data professionals and shorten your time to value. Define, categorize, and find all data sets in one place. Share these data sets with other experts with zero codings and drive data-driven insights. This data sharing ability is perfect for companies that want to store their data once, share it with other experts, and use it multiple times, now and in the future. Define dataset, apply SQL transformations or simply migrate your SQL data processing logic to any cloud data warehouse. -
23
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. -
24
IBM watsonx.data
IBM
Put your data to work, wherever it resides, with the open, hybrid data lakehouse for AI and analytics. Connect your data from anywhere, in any format, and access through a single point of entry with a shared metadata layer. Optimize workloads for price and performance by pairing the right workloads with the right query engine. Embed natural-language semantic search without the need for SQL, so you can unlock generative AI insights faster. Manage and prepare trusted data to improve the relevance and precision of your AI applications. Use all your data, everywhere. With the speed of a data warehouse, the flexibility of a data lake, and special features to support AI, watsonx.data can help you scale AI and analytics across your business. Choose the right engines for your workloads. Flexibly manage cost, performance, and capability with access to multiple open engines including Presto, Presto C++, Spark Milvus, and more. -
25
DataLakeHouse.io
DataLakeHouse.io
DataLakeHouse.io (DLH.io) Data Sync provides replication and synchronization of operational systems (on-premise and cloud-based SaaS) data into destinations of their choosing, primarily Cloud Data Warehouses. Built for marketing teams and really any data team at any size organization, DLH.io enables business cases for building single source of truth data repositories, such as dimensional data warehouses, data vault 2.0, and other machine learning workloads. Use cases are technical and functional including: ELT, ETL, Data Warehouse, Pipeline, Analytics, AI & Machine Learning, Data, Marketing, Sales, Retail, FinTech, Restaurant, Manufacturing, Public Sector, and more. DataLakeHouse.io is on a mission to orchestrate data for every organization particularly those desiring to become data-driven, or those that are continuing their data driven strategy journey. DataLakeHouse.io (aka DLH.io) enables hundreds of companies to managed their cloud data warehousing and analytics solutions.Starting Price: $99 -
26
TIBCO Data Virtualization
TIBCO Software
An enterprise data virtualization solution that orchestrates access to multiple and varied data sources and delivers the datasets and IT-curated data services foundation for nearly any solution. As a modern data layer, the TIBCO® Data Virtualization system addresses the evolving needs of companies with maturing architectures. Remove bottlenecks and enable consistency and reuse by providing all data, on demand, in a single logical layer that is governed, secure, and serves a diverse community of users. Immediate access to all data helps you develop actionable insights and act on them in real time. Users are empowered because they can easily search for and select from a self-service directory of virtualized business data and then use their favorite analytics tools to obtain results. They can spend more time analyzing data, less time searching for it. -
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Kyvos Semantic Layer
Kyvos Insights
Kyvos is a semantic layer for AI and BI. It gives organizations a single, consistent, business-friendly view of their entire data estate. By standardizing how data is defined and understood, Kyvos eliminates metric drift across BI tools and ensures that LLMs and AI agents work with governed business semantics rather than raw tables. Kyvos also delivers lightning-fast analytics at massive scale and high concurrency — including granular multidimensional analysis on the cloud — without the sluggish query times and escalating cloud costs that typically come with it. Kyvos semantic layer provides a unified semantic foundation for AI and BI, standardizing metrics, KPIs, and business logic across tools. It grounds AI in governed business context, eliminates metric drift, and delivers sub-second analytics at scale with high concurrency. It also enables deep multidimensional analysis and reduces cloud costs by serving analytics through its semantic layer. -
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Kylo
Teradata
Kylo is an open source enterprise-ready data lake management software platform for self-service data ingest and data preparation with integrated metadata management, governance, security and best practices inspired by Think Big's 150+ big data implementation projects. Self-service data ingest with data cleansing, validation, and automatic profiling. Wrangle data with visual sql and an interactive transform through a simple user interface. Search and explore data and metadata, view lineage, and profile statistics. Monitor health of feeds and services in the data lake. Track SLAs and troubleshoot performance. Design batch or streaming pipeline templates in Apache NiFi and register with Kylo to enable user self-service. Organizations can expend significant engineering effort moving data into Hadoop yet struggle to maintain governance and data quality. Kylo dramatically simplifies data ingest by shifting ingest to data owners through a simple guided UI. -
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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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BigLake
Google
BigLake is a storage engine that unifies data warehouses and lakes by enabling BigQuery and open-source frameworks like Spark to access data with fine-grained access control. BigLake provides accelerated query performance across multi-cloud storage and open formats such as Apache Iceberg. Store a single copy of data with uniform features across data warehouses & lakes. Fine-grained access control and multi-cloud governance over distributed data. Seamless integration with open-source analytics tools and open data formats. Unlock analytics on distributed data regardless of where and how it’s stored, while choosing the best analytics tools, open source or cloud-native over a single copy of data. Fine-grained access control across open source engines like Apache Spark, Presto, and Trino, and open formats such as Parquet. Performant queries over data lakes powered by BigQuery. Integrates with Dataplex to provide management at scale, including logical data organization.Starting Price: $5 per TB -
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TextQL
TextQL
The platform indexes BI tools and semantic layers, documents data in dbt, and uses OpenAI and language models to provide self-serve power analytics. With TextQL, non-technical users can easily and quickly work with data by asking questions in their work context (Slack/Teams/email) and getting automated answers quickly and safely. The platform also leverages NLP and semantic layers, including the dbt Labs semantic layer, to ensure reasonable solutions. TextQL's elegant handoffs to human analysts, when required, dramatically simplify the whole question-to-answer process with AI. At TextQL, our mission is to empower business teams to access the data that they're looking for in less than a minute. To accomplish this, we help data teams surface and create documentation for their data so that business teams can trust that their reports are up to date. -
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CData Connect AI
CData
CData’s AI offering is centered on Connect AI and associated AI-driven connectivity capabilities, which provide live, governed access to enterprise data without moving it off source systems. Connect AI is built as a managed Model Context Protocol (MCP) platform that lets AI assistants, agents, copilots, and embedded AI applications directly query over 300 data sources, such as CRM, ERP, databases, APIs, with a full understanding of data semantics and relationships. It enforces source system authentication, respects existing role-based permissions, and ensures that AI actions (reads and writes) follow governance and audit rules. The system supports query pushdown, parallel paging, bulk read/write operations, streaming mode for large datasets, and cross-source reasoning via a unified semantic layer. In addition, CData’s “Talk to your Data” engine integrates with its Virtuality product to allow conversational access to BI insights and reports. -
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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 -
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Codd AI
Codd AI
Codd AI solves one of the biggest problems in analytics: making data truly business-ready. Instead of teams spending weeks manually mapping schemas, building models, and defining metrics, Codd uses generative AI to automatically create a context-aware semantic layer that aligns technical data with your business language. That means business users can ask questions in plain English and get accurate, governed answers instantly—through BI tools, conversational AI, or any endpoint. With governance and auditability built in, Codd makes analytics faster, clearer, and more trustworthy. Codd AI ingests both technical metadata from your database, as well as business rules and logic to use AI to auto-generate the most comprehensive semantic layer. This semantic layer is embedded in an intelligent query agent to power natural language (NLP) conversational analytics or power traditional BI toolsStarting Price: $25k per year -
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Cube
Cube Dev
Cube is a platform that provides a universal semantic layer to simplify and unify enterprise data management and analytics. By transforming how data is managed, Cube eliminates the need for inconsistent models and metrics, delivering trusted data to users while making it AI-ready. This platform helps organizations scale their data infrastructure by integrating disparate data sources and creating consistent metrics that can be used across teams. Cube is designed for enterprises looking to enhance their analytics capabilities, make their data accessible, and power AI-driven insights with ease. -
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Dataplex Universal Catalog
Google
Dataplex Universal Catalog is Google Cloud’s intelligent governance platform for data and AI artifacts. It centralizes discovery, management, and monitoring across data lakes, warehouses, and databases, giving teams unified access to trusted data. With Vertex AI integration, users can instantly find datasets, models, features, and related assets in one search experience. It supports semantic search, data lineage, quality checks, and profiling to improve trust and compliance. Integrated with BigQuery and BigLake, it enables end-to-end governance for both proprietary and open lakehouse environments. Dataplex Universal Catalog helps organizations democratize data access, enforce governance, and accelerate analytics and AI initiatives.Starting Price: $0.060 per hour -
37
Brewit
Brewit
Make data-driven decisions 10x faster with self-service analytics. Integrate with your databases and data warehouses all-in-one place (Postgres, MySQL, Snowflake, BigQuery, and more). Brewit can write SQL queries and create recommended charts based on your data questions. It also helps you drill down on the analysis. Chat with your database, visualize insights, & perform analysis. Ensure answer accuracy and consistency with a built-in data catalog. An automated semantic layer that ensures Brewit answers with correct business logic. Easily manage your data catalog & data dictionary. Building a beautiful report is as easy as writing a doc. Data without a story is useless. Our Notion-style notebook editor allows you to create reports & dashboards easily, turning raw data into actionable insights. All organized data products are usable by anyone who has a data question, regardless of their technical skills. -
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MetaCenter
Data Advantage Group
MetaCenter enables business and technology teams to catalog and classify an organization's information assets. Users can self-service questions about their data assets and how data flows through the business and classify how it should be used. This enables organizations to lower costs while improving agility and reducing operational risks. Search-based semantic layer automates cross-referencing models. Faceted Views of specific data assets can be published to individual roles. Lower cost of ownership and higher levels of automation deliver superior ROI compared to competing solutions. Simple GUI driven customization enables rapid application customization. No programming or professional services are required. -
39
BryteFlow
BryteFlow
BryteFlow builds the most efficient automated environments for analytics ever. It converts Amazon S3 into an awesome analytics platform by leveraging the AWS ecosystem intelligently to deliver data at lightning speeds. It complements AWS Lake Formation and automates the Modern Data Architecture providing performance and productivity. You can completely automate data ingestion with BryteFlow Ingest’s simple point-and-click interface while BryteFlow XL Ingest is great for the initial full ingest for very large datasets. No coding is needed! With BryteFlow Blend you can merge data from varied sources like Oracle, SQL Server, Salesforce and SAP etc. and transform it to make it ready for Analytics and Machine Learning. BryteFlow TruData reconciles the data at the destination with the source continually or at a frequency you select. If data is missing or incomplete you get an alert so you can fix the issue easily. -
40
Onehouse
Onehouse
The only fully managed cloud data lakehouse designed to ingest from all your data sources in minutes and support all your query engines at scale, for a fraction of the cost. Ingest from databases and event streams at TB-scale in near real-time, with the simplicity of fully managed pipelines. Query your data with any engine, and support all your use cases including BI, real-time analytics, and AI/ML. Cut your costs by 50% or more compared to cloud data warehouses and ETL tools with simple usage-based pricing. Deploy in minutes without engineering overhead with a fully managed, highly optimized cloud service. Unify your data in a single source of truth and eliminate the need to copy data across data warehouses and lakes. Use the right table format for the job, with omnidirectional interoperability between Apache Hudi, Apache Iceberg, and Delta Lake. Quickly configure managed pipelines for database CDC and streaming ingestion. -
41
Kater.ai
Kater.ai
Kater is built for data professionals and data inquisitors. All organized data products are immediately usable by anyone who has a data question, without knowing a lick of SQL. Kater aims to bridge the ownership of data across all business domains in your company. Butler securely connects to your data warehouse's metadata and objects to help you code, discover data, and so much more. Optimize your data for AI with automatic intelligent labeling, categorization, and data curation. We help you define your semantic layer, metric layer, and general documentation. Validated answers are stored in the query bank for smarter, more accurate responses. -
42
BeagleGPT
BeagleGPT
Proactive data and insights nudges for each user according to their usage pattern, automated heuristic rules, data updates, and user-cohort learnings. The semantic layer is finetuned for organizations with their nomenclatures and terminologies. User roles and preferences are considered while building responses for them. Advanced modules to answer how, why and so what scenarios. A single subscription covers the entire organization, truly propelling data democratization. Beagle is built to nudge you and your team toward data-driven decision-making. It is your personal data assistant that delivers all data-related updates and alerts in your message box. With in-built self-service functionalities, Beagle reduces the total cost of ownership by huge margins. Beagle connects with other dashboards to enhance their power and increase their reach in the organization. -
43
Strategy Mosaic
Strategy Software
Strategy Mosaic is an AI-powered universal semantic data layer and analytics foundation that sits on top of an organization’s existing data systems to unify, govern, and accelerate access to business data for analytics, AI, and reporting without costly restructuring. It creates a single source of truth with consistent business definitions, metrics, and security policies across tools and sources, harmonizing data from hundreds of systems so insights are reliable and comparable everywhere. Built with AI-assisted data modeling (Mosaic Studio), Mosaic automates data preparation, cleansing, enrichment, and modeling, reducing the time and effort needed to build robust data products and semantic models. Its universal connectors let users access governed data via SQL, REST, Python, or through popular BI and productivity tools like Power BI, Tableau, Excel, and Google Sheets, while an in-memory acceleration engine delivers fast query performance across diverse sources. -
44
SAP Datasphere
SAP
SAP Datasphere is a unified data experience platform within SAP Business Data Cloud, designed to provide seamless, scalable access to mission-critical business data. It integrates data from SAP and non-SAP systems, harmonizing diverse data landscapes and enabling faster, more accurate decision-making. With capabilities like data federation, cataloging, semantic modeling, and real-time data integration, SAP Datasphere ensures that businesses have consistent, contextualized data across hybrid and cloud environments. The platform simplifies data management by preserving business context and logic, providing a comprehensive view of data that drives innovation and enhances business processes. -
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Baidu Palo
Baidu AI Cloud
Palo helps enterprises to create the PB-level MPP architecture data warehouse service within several minutes and import the massive data from RDS, BOS, and BMR. Thus, Palo can perform the multi-dimensional analytics of big data. Palo is compatible with mainstream BI tools. Data analysts can analyze and display the data visually and gain insights quickly to assist decision-making. It has the industry-leading MPP query engine, with column storage, intelligent index,and vector execution functions. It can also provide in-library analytics, window functions, and other advanced analytics functions. You can create a materialized view and change the table structure without the suspension of service. It supports flexible and efficient data recovery. -
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Data Virtuality
Data Virtuality
Connect and centralize data. Transform your existing data landscape into a flexible data powerhouse. Data Virtuality is a data integration platform for instant data access, easy data centralization and data governance. Our Logical Data Warehouse solution combines data virtualization and materialization for the highest possible performance. Build your single source of data truth with a virtual layer on top of your existing data environment for high data quality, data governance, and fast time-to-market. Hosted in the cloud or on-premises. Data Virtuality has 3 modules: Pipes, Pipes Professional, and Logical Data Warehouse. Cut down your development time by up to 80%. Access any data in minutes and automate data workflows using SQL. Use Rapid BI Prototyping for significantly faster time-to-market. Ensure data quality for accurate, complete, and consistent data. Use metadata repositories to improve master data management. -
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Upsolver
Upsolver
Upsolver makes it incredibly simple to build a governed data lake and to manage, integrate and prepare streaming data for analysis. Define pipelines using only SQL on auto-generated schema-on-read. Easy visual IDE to accelerate building pipelines. Add Upserts and Deletes to data lake tables. Blend streaming and large-scale batch data. Automated schema evolution and reprocessing from previous state. Automatic orchestration of pipelines (no DAGs). Fully-managed execution at scale. Strong consistency guarantee over object storage. Near-zero maintenance overhead for analytics-ready data. Built-in hygiene for data lake tables including columnar formats, partitioning, compaction and vacuuming. 100,000 events per second (billions daily) at low cost. Continuous lock-free compaction to avoid “small files” problem. Parquet-based tables for fast queries. -
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Datameer
Datameer
Datameer revolutionizes data transformation with a low-code approach, trusted by top global enterprises. Craft, transform, and publish data seamlessly with no code and SQL, simplifying complex data engineering tasks. Empower your data teams to make informed decisions confidently while saving costs and ensuring responsible self-service analytics. Speed up your analytics workflow by transforming datasets to answer ad-hoc questions and support operational dashboards. Empower everyone on your team with our SQL or Drag-and-Drop to transform your data in an intuitive and collaborative workspace. And best of all, everything happens in Snowflake. Datameer is designed and optimized for Snowflake to reduce data movement and increase platform adoption. Some of the problems Datameer solves: - Analytics is not accessible - Drowning in backlog - Long development -
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Presto
Presto Foundation
Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes. For data engineers who struggle with managing multiple query languages and interfaces to siloed databases and storage, Presto is the fast and reliable engine that provides one simple ANSI SQL interface for all your data analytics and your open lakehouse. Different engines for different workloads means you will have to re-platform down the road. With Presto, you get 1 familar ANSI SQL language and 1 engine for your data analytics so you don't need to graduate to another lakehouse engine. Presto can be used for interactive and batch workloads, small and large amounts of data, and scales from a few to thousands of users. Presto gives you one simple ANSI SQL interface for all of your data in various siloed data systems, helping you join your data ecosystem together. -
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Microsoft Fabric
Microsoft
Reshape how everyone accesses, manages, and acts on data and insights by connecting every data source and analytics service together—on a single, AI-powered platform. All your data. All your teams. All in one place. Establish an open and lake-centric hub that helps data engineers connect and curate data from different sources—eliminating sprawl and creating custom views for everyone. Accelerate analysis by developing AI models on a single foundation without data movement—reducing the time data scientists need to deliver value. Innovate faster by helping every person in your organization act on insights from within Microsoft 365 apps, such as Microsoft Excel and Microsoft Teams. Responsibly connect people and data using an open and scalable solution that gives data stewards additional control with built-in security, governance, and compliance.Starting Price: $156.334/month/2CU
