Alternatives to HugeGraph
Compare HugeGraph alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to HugeGraph in 2026. Compare features, ratings, user reviews, pricing, and more from HugeGraph competitors and alternatives in order to make an informed decision for your business.
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1
Vertex AI
Google
Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection. Vertex AI Agent Builder enables developers to create and deploy enterprise-grade generative AI applications. It offers both no-code and code-first approaches, allowing users to build AI agents using natural language instructions or by leveraging frameworks like LangChain and LlamaIndex. -
2
Apache TinkerPop
Apache Software Foundation
Apache TinkerPop™ is a graph computing framework for both graph databases (OLTP) and graph analytic systems (OLAP). Gremlin is the graph traversal language of Apache TinkerPop. Gremlin is a functional, data-flow language that enables users to succinctly express complex traversals on (or queries of) their application's property graph. Every Gremlin traversal is composed of a sequence of (potentially nested) steps. A graph is a structure composed of vertices and edges. Both vertices and edges can have an arbitrary number of key/value pairs called properties. Vertices denote discrete objects such as a person, a place, or an event. Edges denote relationships between vertices. For instance, a person may know another person, have been involved in an event, and/or have recently been at a particular place. If a user's domain is composed of a heterogeneous set of objects (vertices) that can be related to one another in a multitude of ways (edges).Starting Price: Free -
3
G.V() Gremlin IDE
gdotv Ltd
G.V() is an all-in-one Gremlin IDE to write, debug, test and analyze results for your Gremlin graph database. It offers rich a UI with smart autocomplete, graph visualization, editing and connection management. G.V() automatically detects your connection setting requirements based on the hostname you provide and prompts you for the next required information for an easy onboarding experience, regardless of which Gremlin database you're using. Load, visualize and draw your graph in true “What You See Is What You Get” fashion to build, test, visualize and query your data easily. Learn Gremlin with the embedded documentation and G.V()'s in-memory graph. View your Gremlin query results in various formats allowing to test, navigate and understand your query results rapidly. Compatible with all major Apache TinkerPop enabled Graph Database Providers: Amazon Neptune, Azure Cosmos DB’s Gremlin API, DataStax Enterprise Graph, JanusGraph, ArcadeDB, Aliyun TairForGraph and Gremlin Server. -
4
Amazon Neptune
Amazon
Amazon Neptune is a fast, reliable, fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Amazon Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency. Amazon Neptune supports popular graph models Property Graph and W3C's RDF, and their respective query languages Apache TinkerPop Gremlin and SPARQL, allowing you to easily build queries that efficiently navigate highly connected datasets. Neptune powers graph use cases such as recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security. Proactively detect and investigate IT infrastructure using a layered security approach. Visualize all infrastructure to plan, predict and mitigate risk. Build graph queries for near-real-time identity fraud pattern detection in financial and purchase transactions. -
5
ArcadeDB
ArcadeDB
ArcadeDB is an open-source, next-generation multi-model database. Forget Polyglot Persistence — store graphs, documents, key-value pairs, search engine indexes, vectors, and time-series data all in one database with native support for every model. No translation layers, no performance penalties. Process over 10 million records per second. Traversal speed stays constant whether your database has hundreds or billions of records. Query in the language you prefer: SQL, Cypher, Gremlin, GraphQL, MongoDB API, or Java. Deploy ArcadeDB embedded in your JVM application, on a standalone server, or distributed across multiple nodes with Raft Consensus for high availability. Fully ACID-compliant. Super lightweight. Apache 2.0 licensed — free for production and commercial use.Starting Price: Free -
6
Cayley
Cayley
Cayley is an open-source database for Linked Data. It is inspired by the graph database behind Google's Knowledge Graph (formerly Freebase). Cayley is an open-source graph database designed for ease of use and storing complex data. Built-in query editor, visualizer and REPL. Cayley can use multiple query languages like Gizmo, a query language inspired by Gremlin, GraphQL-inspired query language, MQL a simplified version for Freebase fans. Cayley is modular, easy to connect to your favorite programming languages and back-end stores, production ready, well tested and used by various companies for their production workloads and fast with optimized specifically for usage in applications. Rough performance testing shows that, on 2014 consumer hardware and an average disk, 134m quads in LevelDB is no problem and a multi-hop intersection query- films starring X and Y - takes ~150ms. Cayley is configured by default to run in memory (That's what backend memstore means). -
7
KgBase
KgBase
KgBase, or Knowledge Graph Base, is a collaborative, robust database with versioning, analytics & visualizations. With KgBase, any community or individual can create knowledge graphs to build insights about their data. Import your CSVs and spreadsheets, or use our API to work on data together. Build no-code knowledge graphs with KgBase, our easy-to-use UI lets you traverse the graph, show the results as tables and charts, and much more. Play with your graph data. Build your query and see results update in real time. It's like writing query code in Cypher or Gremlin, except easier. And fast. Your graph can be viewed as a table, allowing you to browse all results - no matter the size. KgBase works great with large graphs (millions of nodes), as well as simple projects. In the cloud, or self-hosted, with wide database support. Introduce graphs into your organization by seeding graph from a template. Results of any query can be easily turned into a chart visualization.Starting Price: $19 per month -
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JanusGraph
JanusGraph
JanusGraph is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. JanusGraph is a project under The Linux Foundation, and includes participants from Expero, Google, GRAKN.AI, Hortonworks, IBM and Amazon. Elastic and linear scalability for a growing data and user base. Data distribution and replication for performance and fault tolerance. Multi-datacenter high availability and hot backups. All functionality is totally free. No need to buy commercial licenses. JanusGraph is fully open source under the Apache 2 license. JanusGraph is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time. Support for ACID and eventual consistency. In addition to online transactional processing (OLTP), JanusGraph supports global graph analytics (OLAP) with its Apache Spark integration. -
9
Graphlytic
Demtec
Graphlytic is a customizable web platform for knowledge graph visualization and analysis. Users can interactively explore the graph, look for patterns with the Cypher or Gremlin query languages (or query templates for non-tech users), or use filters to find the answers to any graph question. The graph visualization brings deep insights in industries, such as scientific research, anti-fraud investigation, etc. Users with very little graph theory knowledge can start to explore the data in no time. Graph rendering is done with the Cytoscape.js library which allows us to render tens of thousands of nodes and hundreds of thousands of relationships. The application is provided in three ways: Desktop, Cloud, and Server. Graphlytic Desktop is a free Neo4j Desktop application installed in just a few clicks. Cloud instances are ideal for small teams that don't want to worry about the installation and need to get up and running in very little time.Starting Price: 19 EUR/month -
10
InfiniteGraph
Objectivity
InfiniteGraph is a massively scalable graph database specifically designed to excel at high-speed ingest of massive volumes of data (billions of nodes and edges per hour) while supporting complex queries. InfiniteGraph can seamlessly distribute connected graph data across a global enterprise. InfiniteGraph is a schema-based graph database that supports highly complex data models. It also has an advanced schema evolution capability that allows you to modify and evolve the schema of an existing database. InfiniteGraph’s Placement Management Capability allows you to optimize the placement of data items resulting in tremendous performance improvements in both query and ingest. InfiniteGraph has client-side caching which caches frequently used node and edges. InfiniteGraph's DO query language enables complex "beyond graph" queries not supported by other query languages. -
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AnzoGraph DB
Cambridge Semantics
With a huge collection of analytical features, AnzoGraph DB can enhance your analytical framework. Watch this video to learn how AnzoGraph DB is a Massively Parallel Processing (MPP) native graph database that is built for data harmonization and analytics. Horizontally scalable graph database built for online analytics and data harmonization. Take on data harmonization and linked data challenges with AnzoGraph DB, a market-leading analytical graph database. AnzoGraph DB provides industrialized online performance for enterprise-scale graph applications. AnzoGraph DB uses familiar SPARQL*/OWL for semantic graphs but also supports Labeled Property Graphs (LPGs). Access to many analytical, machine learning and data science capabilities help you achieve new insights, delivered at unparalleled speed and scale. Use context and relationships between data as first-class citizens in your analysis. Ultra-fast data loading and analytical queries. -
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RushDB
RushDB
RushDB is an open-source zero-configuration graph database that instantly transforms JSON and CSV into a fully normalized, queryable Neo4j graph - without the overhead of schema design, migrations, or manual indexing. Designed for modern applications, AI, and ML workflows, RushDB provides a frictionless developer experience, combining the flexibility of NoSQL with the structured power of relational databases. With automatic data normalization, ACID compliance, and a powerful API, RushDB eliminates the complexities of data ingestion, relationship management, and query optimization - so you can focus on building, not database administration. Key Features: 1. Zero Configuration, Instant Data Ingestion 2. Graph-Powered Storage & Queries 3. ACID Transactions & Schema Evolution 4. Developer-Centric API: Query Like an SDK 5. High-Performance Search & Analytics 6. Self-Hosted or Cloud-ReadyStarting Price: $9/month -
13
Apache Phoenix
Apache Software Foundation
Apache Phoenix enables OLTP and operational analytics in Hadoop for low-latency applications by combining the best of both worlds. The power of standard SQL and JDBC APIs with full ACID transaction capabilities and the flexibility of late-bound, schema-on-read capabilities from the NoSQL world by leveraging HBase as its backing store. Apache Phoenix is fully integrated with other Hadoop products such as Spark, Hive, Pig, Flume, and Map Reduce. Become the trusted data platform for OLTP and operational analytics for Hadoop through well-defined, industry-standard APIs. Apache Phoenix takes your SQL query, compiles it into a series of HBase scans, and orchestrates the running of those scans to produce regular JDBC result sets. Direct use of the HBase API, along with coprocessors and custom filters, results in performance on the order of milliseconds for small queries, or seconds for tens of millions of rows.Starting Price: Free -
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Apache Giraph
Apache Software Foundation
Apache Giraph is an iterative graph processing system built for high scalability. For example, it is currently used at Facebook to analyze the social graph formed by users and their connections. Giraph originated as the open-source counterpart to Pregel, the graph processing architecture developed at Google and described in a 2010 paper. Both systems are inspired by the Bulk Synchronous Parallel model of distributed computation introduced by Leslie Valiant. Giraph adds several features beyond the basic Pregel model, including master computation, sharded aggregators, edge-oriented input, out-of-core computation, and more. With a steady development cycle and a growing community of users worldwide, Giraph is a natural choice for unleashing the potential of structured datasets at a massive scale. Apache Giraph is an iterative graph processing framework, built on top of Apache Hadoop. -
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GraphDB
Ontotext
*GraphDB allows you to link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs.* GraphDB is a highly efficient and robust graph database with RDF and SPARQL support. The GraphDB database supports a highly available replication cluster, which has been proven in a number of enterprise use cases that required resilience in data loading and query answering. If you need a quick overview of GraphDB or a download link to its latest releases, please visit the GraphDB product section. GraphDB uses RDF4J as a library, utilizing its APIs for storage and querying, as well as the support for a wide variety of query languages (e.g., SPARQL and SeRQL) and RDF syntaxes (e.g., RDF/XML, N3, Turtle). -
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DataStax
DataStax
The Open, Multi-Cloud Stack for Modern Data Apps. Built on open-source Apache Cassandra™. Global-scale and 100% uptime without vendor lock-in. Deploy on multi-cloud, on-prem, open-source, and Kubernetes. Elastic and pay-as-you-go for improved TCO. Start building faster with Stargate APIs for NoSQL, real-time, reactive, JSON, REST, and GraphQL. Skip the complexity of multiple OSS projects and APIs that don’t scale. Ideal for commerce, mobile, AI/ML, IoT, microservices, social, gaming, and richly interactive applications that must scale-up and scale-down with demand. Get building modern data applications with Astra, a database-as-a-service powered by Apache Cassandra™. Use REST, GraphQL, JSON with your favorite full-stack framework Richly interactive apps that are elastic and viral-ready from Day 1. Pay-as-you-go Apache Cassandra DBaaS that scales effortlessly and affordably. -
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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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RecallGraph
RecallGraph
RecallGraph is a versioned-graph data store - it retains all changes that its data (vertices and edges) have gone through to reach their current state. It supports point-in-time graph traversals, letting the user query any past state of the graph just as easily as the present. RecallGraph is a potential fit for scenarios where data is best represented as a network of vertices and edges (i.e., a graph) having the following characteristics: 1. Both vertices and edges can hold properties in the form of attribute/value pairs (equivalent to JSON objects). 2. Documents (vertices/edges) mutate within their lifespan (both in their individual attributes/values and in their relations with each other). 3. Past states of documents are as important as their present, necessitating retention and queryability of their change history. Also see this blog post for an intro - https://blog.recallgraph.tech/never-lose-your-old-data-again. -
19
ArangoDB
ArangoDB
Natively store data for graph, document and search needs. Utilize feature-rich access with one query language. Map data natively to the database and access it with the best patterns for the job – traversals, joins, search, ranking, geospatial, aggregations – you name it. Polyglot persistence without the costs. Easily design, scale and adapt your architectures to changing needs and with much less effort. Combine the flexibility of JSON with semantic search and graph technology for next generation feature extraction even for large datasets. -
20
FalkorDB
FalkorDB
FalkorDB is an ultra-fast, multi-tenant graph database optimized for GraphRAG, delivering accurate, relevant AI/ML results with reduced hallucinations and enhanced performance. It leverages sparse matrix representations and linear algebra to efficiently handle complex, interconnected data in real-time, resulting in fewer hallucinations and more accurate responses from large language models. FalkorDB supports the OpenCypher query language with proprietary enhancements, enabling expressive and efficient querying of graph data. It offers built-in vector indexing and full-text search capabilities, allowing for complex searches and similarity matching within the same database environment. FalkorDB's architecture includes multi-graph support, enabling multiple isolated graphs within a single instance, ensuring security and performance across tenants. It also provides high availability with live replication, ensuring data is always accessible. -
21
ent
ent
An entity framework for Go. Simple, yet powerful ORM for modeling and querying data. Simple API for modeling any database schema as Go objects. Run queries, and aggregations and traverse any graph structure easily. 100% statically typed and explicit API using code generation. The latest version of Ent now includes a type-safe API enabling ordering by fields and edges. This API will soon be available in our GraphQL integration too. You can now visualize your Ent schema as an ERD with one command. The API enables you to easily integrate features such as logging, tracing, caching, and even implementing soft deletion with 20 lines of code! The Ent framework supports GraphQL using the 99designs/gqlgen library and provides various integrations. Generating a GraphQL schema for nodes and edges defined in an Ent schema. Efficient field collection to overcome the N+1 problem without requiring data loaders.Starting Price: Free -
22
Apache Spark
Apache Software Foundation
Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources. -
23
Graph Engine
Microsoft
Graph Engine (GE) is a distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine. The distributed RAM store provides a globally addressable high-performance key-value store over a cluster of machines. Through the RAM store, GE enables the fast random data access power over a large distributed data set. The capability of fast data exploration and distributed parallel computing makes GE a natural large graph processing platform. GE supports both low-latency online query processing and high-throughput offline analytics on billion-node large graphs. Schema does matter when we need to process data efficiently. Strongly-typed data modeling is crucial for compact data storage, fast data access, and clear data semantics. GE is good at managing billions of run-time objects of varied sizes. One byte counts as the number of objects goes large. GE provides fast memory allocation and reallocation with high memory ratios. -
24
Nebula Graph
vesoft
The graph database built for super large-scale graphs with milliseconds of latency. We are continuing to collaborate with the community to prepare, popularize and promote the graph database. Nebula Graph only allows authenticated access via role-based access control. Nebula Graph supports multiple storage engine types and the query language can be extended to support new algorithms. Nebula Graph provides low latency read and write , while still maintaining high throughput to simplify the most complex data sets. With a shared-nothing distributed architecture , Nebula Graph offers linear scalability. Nebula Graph's SQL-like query language is easy to understand and powerful enough to meet complex business needs. With horizontal scalability and a snapshot feature, Nebula Graph guarantees high availability even in case of failures. Large Internet companies like JD, Meituan, and Xiaohongshu have deployed Nebula Graph in production environments. -
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TIBCO Graph Database
TIBCO
To unveil the true value of constantly evolving business data, you need to understand the relationships in data in a much more profound way. Unlike other databases, a graph database puts relationships at the forefront, using Graph theory and Linear Algebra to traverse and show how complex data webs, data sources, and data points relate. TIBCO® Graph Database allows you to discover, store, and convert complex dynamic data into meaningful insights. Enable users to rapidly build data and computational models that establish dynamic relationships among organizational silos. These knowledge graphs deliver value by connecting your organization’s vast array of data and revealing relationships that let you accelerate optimization of assets and processes. Combined OLTP and OLAP features in a single enterprise-grade database. Optimistic ACID level transaction properties with native storage and access. -
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Grakn
Grakn Labs
Building intelligent systems starts at the database. Grakn is an intelligent database - a knowledge graph. An insanely intuitive & expressive data schema, with constructs to define hierarchies, hyper-entities, hyper-relations and rules, to build rich knowledge models. An intelligent language that performs logical inference of data types, relationships, attributes and complex patterns, during runtime, and over distributed & persisted data. Out-of-the-box distributed analytics (Pregel and MapReduce) algorithms, accessible through the language through simple queries. Strong abstraction over low-level patterns, enabling simpler expressions of complex constructs, while the system figures out the most optimal query execution. Scale your enterprise Knowledge Graph with Grakn KGMS and Workbase. A distributed database designed to scale over a network of computers through partitioning and replication. -
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Luna for Apache Cassandra
DataStax
Luna is a subscription to the Apache Cassandra support and expertise at DataStax. It allows you to enjoy all the benefits of open-source Cassandra, with the peace of mind knowing you have direct access to the team that authored the majority of the code and supported some of the largest deployments in the world. Best practices, advice, and SLA-based support to keep your Cassandra deployment in top shape. Scale without compromising on performance or latency to seamlessly manage the most demanding real-time workloads. Create real-time and highly-interactive customer experiences with blisteringly fast read and writes. Luna provides assistance with resolving issues and following best practices with Cassandra clusters. Services provide help through the full application life cycle, with a deeper integration in your team working together on implementation. -
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TigerGraph
TigerGraph
Through its Native Parallel Graph™ technology, the TigerGraph™ graph platform represents what’s next in the graph database evolution: a complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time. Combining the best ideas (MapReduce, Massively Parallel Processing, and fast data compression/decompression) with fresh development, TigerGraph delivers what you’ve been waiting for: the speed, scalability, and deep exploration/querying capability to extract more business value from your data. -
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Oracle Spatial and Graph
Oracle
Graph databases, part of Oracle’s converged database offering, eliminate the need to set up a separate database and move data. Analysts and developers can perform fraud detection in banking, find connections and link to data, and improve traceability in smart manufacturing, all while gaining enterprise-grade security, ease of data ingestion, and strong support for data workloads. Oracle Autonomous Database includes Graph Studio, with one-click provisioning, integrated tooling, and security. Graph Studio automates graph data management and simplifies modeling, analysis, and visualization across the graph analytics lifecycle. Oracle provides support for both property and RDF knowledge graphs, and simplifies the process of modeling relational data as graph structures. Interactive graph queries can run directly on graph data or in a high-performance in-memory graph server. -
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Gato GraphQL
Gato GraphQL
Gato GraphQL is a powerful and flexible GraphQL server for WordPress, enabling users to access and manipulate any piece of data, such as posts, users, comments, tags, and categories, via a GraphQL API. It supports building dynamic, headless sites by using WordPress as the CMS to manage data while allowing the use of any framework for rendering. It offers multiple interactive clients, including GraphiQL and Voyager, providing user-friendly interfaces for composing queries and visualizing the schema. Security features include granular access control based on user roles or IP addresses, HTTP caching for performance optimization, and the ability to create public, private, and password-protected endpoints. Gato GraphQL also supports nested mutations, custom endpoints, persisted queries, and field deprecation via the UI. Additionally, it integrates with popular WordPress plugins and external services, extending the GraphQL schema's capabilities. Starting Price: $249 one-time payment -
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Fluree
Fluree
Fluree is an immutable RDF graph database written in Clojure and adhering to W3C standards, supporting JSON and JSON-LD while accommodating various RDF ontologies; it boasts a scalable, cloud-native architecture utilizing a lightweight Java runtime, with individually scalable ledger and graph database components, embodying a "Data-Centric" ideology that treats data as a reusable asset independent of singular applications, underpinned by an immutable ledger that secures transactions with cryptographic integrity, alongside a rich RDF graph database capable of various queries, and employs SmartFunctions for enforcing data management rules, including identity and access management and data quality. -
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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 -
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VelocityDB
VelocityDB
VelocityDB is a database engine like no other. It can store data faster and more efficiently than any other solution at a fraction of the cost of other database engines. It stores .NET objects as they are with no mapping to tables, JSON or XML. VelocityGraph is an add on open source property graph database that can be used in conjunction with the VelocityDB object database. Object and graph database engine VelocityDB is a C# .NET noSQL object fatabase, extended as graph database is VelocityGraph. World’s fastest most scalable & flexible database. A bug reported with a reproducible test case is usually fixed within a week. The most important benefit is the flexibility that this database system provides. No other types of database system lets you fine tune your application to the finest details. Using VelocityDB, you can choose the best possible data structures for your application. You can control where you place the data persistently and how it's indexed and accessed.Starting Price: $200 per 6 moths -
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Dgraph
Hypermode
Dgraph is an open source, low-latency, high throughput, native and distributed graph database. Designed to easily scale to meet the needs of small startups as well as large companies with massive amounts of data, DGraph can handle terabytes of structured data running on commodity hardware with low latency for real time user queries. It addresses business needs and uses cases involving diverse social and knowledge graphs, real-time recommendation engines, semantic search, pattern matching and fraud detection, serving relationship data, and serving web apps. -
35
Neo4j
Neo4j
Neo4j’s graph data platform is purpose-built to leverage not only data but also data relationships. Using Neo4j, developers build intelligent applications that traverse today's large, interconnected datasets in real time. Powered by a native graph storage and processing engine, Neo4j’s graph database delivers an intuitive, flexible and secure database for unique, actionable insights. -
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Memgraph
Memgraph
Memgraph offers a light and powerful graph platform comprising the Memgraph Graph Database, MAGE Library, and Memgraph Lab Visualization. Memgraph is a dynamic, lightweight graph database optimized for analyzing data, relationships, and dependencies quickly and efficiently. It comes with a rich suite of pre-built deep path traversal algorithms and a library of traditional, dynamic, and ML algorithms tailored for advanced graph analysis, making Memgraph an excellent choice in critical decision-making scenarios such as risk assessment (fraud detection, cybersecurity threat analysis, and criminal risk assessment), 360-degree data and network exploration (Identity and Access Management (IAM), Master Data Management (MDM), Bill of Materials (BOM)), and logistics and network optimization. -
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The Graph
The Graph
APIs for a vibrant decentralized future. The Graph is an indexing protocol for querying networks like Ethereum and IPFS. Anyone can build and publish open APIs, called subgraphs, making data easily accessible. Subgraphs can be composed into a global graph of all the world's public information. This data can be transformed, organized, and shared across applications for anyone to query with just a few keystrokes. Before The Graph, teams had to develop and operate proprietary indexing servers. This required significant engineering and hardware resources and broke the important security properties required for decentralization. -
38
HyperGraphDB
Kobrix Software
HyperGraphDB is a general purpose, open-source data storage mechanism based on a powerful knowledge management formalism known as directed hypergraphs. While a persistent memory model designed mostly for knowledge management, AI and semantic web projects, it can also be used as an embedded object-oriented database for Java projects of all sizes. Or a graph database, or a (non-SQL) relational database. HyperGraphDB is a storage framework based on generalized hypergraphs as its underlying data model. The unit of storage is a tuple made up of 0 or more other tuples. Each such tuple is called an atom. One could think of the data model as relational where higher-order, n-ary relationships are allowed or as graph-oriented where edges can point to an arbitrary set of nodes and other edges. Each atom has an arbitrary, strongly-typed value associated with it. The type system managing those values is embedded as a hypergraph and customizable from the ground up. -
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GraphBase
FactNexus
GraphBase is a Graph Database Management System (Graph DBMS) engineered to simplify the creation and maintenance of complex data graphs. Complex and highly-connected structures are a challenge for the Relational Database Management System (RDBMS). A graph database provides much better modelling utility, performance and scalability. The current crop of graph database products - the triplestores and property graphs - have been around for nearly two decades. They're powerful tools, they have many uses, but they're still not suited to the management of complex data structures. With GraphBase, our goal was to simplify the management of complex data structures, so that your data could become something more. It could become Knowledge. We achieved this by redefining how graph data should be managed. In GraphBase, the graph is a first-class citizen. You get a graph equivalent of the "rows and tables" paradigm that makes a Relational Database so easy to use. -
40
AllegroGraph
Franz Inc.
AllegroGraph is a breakthrough solution that allows infinite data integration through a patented approach unifying all data and siloed knowledge into an Entity-Event Knowledge Graph solution that can support massive big data analytics. AllegroGraph utilizes unique federated sharding capabilities that drive 360-degree insights and enable complex reasoning across a distributed Knowledge Graph. AllegroGraph provides users with an integrated version of Gruff, a unique browser-based graph visualization software tool for exploring and discovering connections within enterprise Knowledge Graphs. Franz’s Knowledge Graph Solution includes both technology and services for building industrial strength Entity-Event Knowledge Graphs based on best-of-class tools, products, knowledge, skills and experience. -
41
ApertureDB
ApertureDB
Build your competitive edge with the power of vector search. Streamline your AI/ML pipeline workflows, reduce infrastructure costs, and stay ahead of the curve with up to 10x faster time-to-market. Break free of data silos with ApertureDB's unified multimodal data management, freeing your AI teams to innovate. Set up and scale complex multimodal data infrastructure for billions of objects across your entire enterprise in days, not months. Unifying multimodal data, advanced vector search, and innovative knowledge graph with a powerful query engine to build AI applications faster at enterprise scale. ApertureDB can enhance the productivity of your AI/ML teams and accelerate returns from AI investment with all your data. Try it for free or schedule a demo to see it in action. Find relevant images based on labels, geolocation, and regions of interest. Prepare large-scale multi-modal medical scans for ML and clinical studies.Starting Price: $0.33 per hour -
42
Maana Knowledge Platform
Maana
Build your Knowledge Layer with a highly-intuitive visual experience. Create and query the knowledge graph. Hydrate domain concepts in the knowledge graph with data. Trigger bots to enrich the knowledge graph with dynamic links. Create and compose services with function composition features. Add and orchestrate services on the knowledge graph. Provides interactive and scripted access to convenient system actions. Schema management, data loading, querying and administration. The command line interface is easily extensible with custom plug-ins. Allows extendibility with custom plugins making it easy for developers to add functionality. Knowledge applications are use cases developed by customers on Maana platform. They provide AI-driven recommendations into operational decisions. A knowledge application is made up by decision models that perform real-time calculations. A customer does not have access to knowledge applications developed by other customers. -
43
SQLPilot
SQLPilot
Write your prompt in natural language, mention the tables required, and generate a query with the AI model of your choice. Add as many connections as you want. Supports autocomplete for SQL queries to speed up your workflow. We do not store your schemas, queries, or credentials. We only use the data you provide to us to generate SQL queries. Download your results in CSV format. View your results in graphs and charts. Experience the power of AI-powered SQL queries with our free plan. Quickly generate your complex SQL queries with the help of AI. SQLPilot is your AI-first SQL query tool to generate queries with all the context you need.Starting Price: $20 per month -
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Back4app
Back4app
Store and query relational data on the cloud. Make it accessible over GraphQL and REST with a scalable, open-source backend. Store and query relational data through GraphQL, REST, or Parse SDKs. Add business logic using cloud functions. Make apps faster without managing infrastructure. Build relational data models in minutes, and perform complex relational queries in a truly serverless platform. Our engineer team is ready to guide you on each step of the process. From database to cloud functions we help you to migrate in the smoothest way. Keep costs in check even when you scale your apps with affordable, predictable pricing. Scaling happens automatically and, we guide the process to ensure that nothing goes wrong. Build your app exactly the way you'd like, without getting bogged down in the backend. Of course, you do. Keeping data safe is more important than ever.Starting Price: $4.99 per month -
45
GraphQL
The GraphQL Foundation
GraphQL is a query language for APIs and a runtime for fulfilling those queries with your existing data. GraphQL provides a complete and understandable description of the data in your API, gives clients the power to ask for exactly what they need and nothing more, makes it easier to evolve APIs over time, and enables powerful developer tools. Send a GraphQL query to your API and get exactly what you need, nothing more and nothing less. GraphQL queries always return predictable results. Apps using GraphQL are fast and stable because they control the data they get, not the server. GraphQL queries access not just the properties of one resource but also smoothly follow references between them. While typical REST APIs require loading from multiple URLs, GraphQL APIs get all the data your app needs in a single request. Apps using GraphQL can be quick even on slow mobile network connections. -
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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. -
47
Sparksee
Sparsity Technologies
Sparksee (formerly known as DEX), makes space and performance compatible with a small footprint and a fast analysis of large networks. It is natively available for .Net, C++, Python, Objective-C and Java, and covers the whole spectrum of Operating Systems. The graph is represented through bitmap data structures that allow high compression rates. Each of the bitmaps is partitioned into chunks that fit into disk pages to improve I/O locality. Using bitmaps, operations are computed with binary logic instructions that simplify the execution in pipelined processors. Full native indexing allows an extremely fast access to each of the graph data structures. Node adjacencies are represented by bitmaps to minimize their footprint. The number of times each data page is brought to memory is minimized with advanced I/O policies. Each value in the database is represented only once, avoiding unnecessary replication. -
48
Graph Story
Graph Story
Companies that opt for a DIY approach for their graph database can expect 2 to 3 months for a production-ready implementation. With Graph Story’s managed service, your production-ready database is available within minutes. Learn more about graph use cases as well as see a comparison between self-hosting and using a managed service. We can deploy where your servers already live: AWS, Azure, or Google Compute Engine, in any region. Need VPC peering or IP-restricted access? Just let us know. We're flexible like that. Building a proof of concept? Fire up a single, enterprise graph instance with a few clicks. Need to move up to a high-availability, production-ready cluster on-demand? We've got you covered! We built graph db management tools so you don't have to! See CPU, Memory and Disk utilization at glance. Get access to configs, logs, backup your database & restore snapshots.Starting Price: $299 per month -
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Virtuoso
OpenLink Software
Virtuoso Universal Server is a modern platform built on existing open standards that harnesses the power of Hyperlinks ( functioning as Super Keys ) for breaking down data silos that impede both user and enterprise ability. Using Virtuoso, you can easily generate financial profile knowledge graphs from near real time financial activity that reduce the cost and complexity associated with detecting fraudent activity patterns. Courtesy of its high-performance, secure, and scalable dbms engine, you can use intelligent reasoning and inference to harmonize fragmented identities using personally identifying attributes such as email addresses, phone numbers, social-security numbers, drivers licenses, etc. for building fraud detection solutions. Virtuoso helps you build powerful solutions applications driven by knowledge graphs derived from a variety of life sciences oriented data sources.Starting Price: $42 per month -
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Blazegraph
Blazegraph
Blazegraph™ DB is a ultra high-performance graph database supporting Blueprints and RDF/SPARQL APIs. It supports up to 50 Billion edges on a single machine. It is in production use for Fortune 500 customers such as EMC, Autodesk, and many others. It is supporting key Precision Medicine applications and has wide-spread usage for life science applications. It is used extensively to support Cyber analytics in commercial and government applications. It powers the Wikimedia Foundation's Wikidata Query Service. You can choose an executable jar, war file, or tar.gz distribution. Blazegraph is designed to be easy to use and get started. It ships without SSL or authentication by default for this reason. For production deployments, we strongly recommend you enable SSL, authentication, and appropriate network configurations. There are some helpful links below to enable you to do this.
