10 Best Graph Databases of 2026

1. 1

   Neo4j

   A native property graph database queried with GQL-compliant Cypher, sold as the managed AuraDB service and as self-managed Community and Enterprise editions.

   9.3overall

   A native property graph database queried with GQL-compliant Cypher, sold as the managed AuraDB service and as self-managed Community and Enterprise editions.

   Best forMost teams building knowledge graphs, GraphRAG and connected-data apps

   Adoption data

   2.8%In the 2026 Stack Overflow Developer Survey, 2.8% of respondents to the database question, or 332 developers, said they had done extensive work with Neo4j, the only dedicated graph database listed in the survey.

   Stack Overflow, 2026 Developer Survey: Databases (2026): “Neo4J 332 2.8%”

   Neo4j is the graph database most developers have used, and the 2026 Stack Overflow survey reflects that: 2.8% of database respondents had worked with it, and no other graph engine made the list. It stores data as nodes and relationships and is queried with Cypher, which Neo4j describes as GQL-compliant, with fully ACID transactions. The managed AuraDB service starts with a free tier that needs no credit card, then AuraDB Professional bills from $0.09 per GB of memory per hour on a minimum 1 GB instance, with up to 128 GB of memory, 2 TB of storage and daily backups kept for 7 days. Business Critical adds multi-zone deployment and a 99.95% uptime SLA from $0.20 per GB per hour. For knowledge graphs and GraphRAG, Neo4j pairs the database with the Graph Data Science library and AI integrations. The self-managed Community Edition is GPLv3 and leaves out automatic high availability and horizontal scaling. We compared documented features and published prices.

   Strengths

   • +AuraDB Free needs no credit card
   • +Neo4j lists 80+ Fortune 100 customers on its homepage
   • +The only graph database in the 2026 Stack Overflow survey's database list, at 2.8%

   Limitations

   • −AuraDB Professional is single-zone; multi-zone needs Business Critical at $0.20 per GB per hour
   • −Community Edition is GPLv3 and lacks automatic high availability and horizontal scaling
   • −AuraDB Free caps node and relationship counts

   SummaryNeo4j is the best choice for most teams modeling connected data because it combines Cypher, a free AuraDB tier and managed instances from $0.09 per GB per hour on all three major clouds. Teams that need RDF and SPARQL should look at GraphDB, Stardog or Amazon Neptune.

2. 2

   Amazon Neptune

   AWS's fully managed graph database service that supports Gremlin, openCypher and SPARQL on one storage engine.

   8.4overall

   AWS's fully managed graph database service that supports Gremlin, openCypher and SPARQL on one storage engine.

   Best forAWS teams that need property graph and RDF queries in one managed service

   Amazon Neptune is the graph option for teams that already run on AWS and want the database managed for them. Its main advantage is breadth of query languages: AWS documents support for Apache TinkerPop Gremlin, openCypher and the W3C's SPARQL, so one service can hold a property graph and an RDF knowledge graph. Each cluster can add up to 15 read replicas next to the primary instance, with point-in-time recovery, continuous backup to Amazon S3 and replication across Availability Zones. Neptune Serverless scales capacity on its own, and Neptune Analytics runs in-memory graph analytics billed by m-NCU, where one m-NCU is a GB of memory for an hour. Pricing is per instance-hour plus storage and I/O; AWS's own worked example puts a db.r5.large at $0.348 per hour, or $250.56 for a 30-day month, with storage at $0.10 per GB-month. New users get 750 free hours on small instances for 30 days, but there is no permanent free tier. We compared documented features and published prices.

   Strengths

   • +One service covers both property graphs and RDF knowledge graphs
   • +Free trial covers 750 hours of db.t3.medium or db.t4g.medium for 30 days
   • +Encryption at rest and in transit, with replication across Availability Zones

   Limitations

   • −Runs only on AWS
   • −Costs add up across instances, storage, I/O and data transfer, so estimates need the AWS calculator
   • −No permanent free tier after the 30-day trial

   SummaryAmazon Neptune is the best choice for AWS teams that need Gremlin, openCypher and SPARQL in one managed database with up to 15 read replicas. Teams outside AWS or on a tight budget should start with Neo4j AuraDB Free or JanusGraph.

3. 3

   FalkorDB

   An open-source, Redis-based property graph database queried with OpenCypher and built for GraphRAG and agent memory.

   8.2overall

   An open-source, Redis-based property graph database queried with OpenCypher and built for GraphRAG and agent memory.

   Best forAI teams that want a low-cost graph for GraphRAG and multi-tenant apps

   Adoption data

   10.5kThe FalkorDB open-source repository on GitHub had 10.5k stars when we checked in November 2026.

   GitHub, FalkorDB/FalkorDB repository (2026): “10.5k stars”

   FalkorDB is a graph database built on Redis that targets AI workloads such as GraphRAG and long-term memory for agents. It follows the openCypher property graph model and adds its own extensions, and it puts full-text, vector and range indexes in the same engine, so a retrieval pipeline can mix graph hops with similarity search. Clients connect over the Redis RESP protocol or Bolt, which helps teams moving from Neo4j drivers. FalkorDB Cloud has a free plan with multi-graph and multi-tenancy, then Startup from $73 per GB per month adds TLS and backups every 12 hours, and Pro from $350 per 8 GB per month adds clustering, high availability and multi-zone deployment. The engine is open source, and the GitHub repository had 10.5k stars when we checked. The speed claims on FalkorDB's site come from its own benchmark against Neo4j, so test your own queries. We compared documented features and published prices.

   Strengths

   • +Free cloud plan includes multi-graph and graph access control
   • +Startup plan from $73 per GB per month adds TLS and backups every 12 hours
   • +Open source and runnable locally with one Docker command

   Limitations

   • −Clustering, high availability and multi-zone start at the Pro plan, from $350 per 8 GB per month
   • −Smaller user base than Neo4j
   • −Speed comparisons on its site are the vendor's own benchmarks

   SummaryFalkorDB is the best choice for AI teams on a budget because it pairs vector and graph indexes with a free cloud plan and a Startup tier from $73 per GB per month. Teams that need high availability should budget for Pro.

4. 4

   NebulaGraph

   An open-source, distributed graph database designed for graphs with hundreds of billions of vertices.

   8.1overall

   An open-source, distributed graph database designed for graphs with hundreds of billions of vertices.

   Best forTeams with very large graphs that want an Apache 2.0 distributed engine

   Adoption data

   12.5kThe NebulaGraph open-source repository on GitHub had 12.5k stars when we checked in November 2026.

   GitHub, vesoft-inc/nebula repository (2026): “12.5k stars”

   NebulaGraph is a distributed graph database that was designed for scale from the start. Its documentation describes it as open source, distributed and native, able to host graphs with hundreds of billions of vertices and trillions of edges while serving queries with millisecond latency. Storage and compute are separate layers that scale on their own, which suits graphs that outgrow a single server. The open-source edition uses nGQL with openCypher compatibility, while the Enterprise Edition and NebulaGraph Cloud add ISO-GQL, vector search and premium support. The core is released under Apache 2.0, and the GitHub repository had 12.5k stars when we checked, which is a sign of a sizable developer community. The weak spot for buyers is pricing: Enterprise and Cloud are quoted on request, so budget planning needs a sales call. Teams that want a familiar Cypher-first workflow may find Neo4j or Memgraph quicker to adopt. We compared documented features and published prices.

   Strengths

   • +Open-source Edition is free under the Apache 2.0 license
   • +Designed from the start as a distributed system
   • +Millisecond-latency queries on very large graphs, per the vendor's docs

   Limitations

   • −Enterprise and Cloud prices are not published
   • −ISO-GQL support is listed only for Enterprise and Cloud
   • −nGQL is a separate language to learn if your team knows Cypher

   SummaryNebulaGraph is the best choice for teams with very large graphs that want a free Apache 2.0 engine that splits storage and compute. Buyers who need a published price should compare Neo4j or TigerGraph.

5. 5

   ArangoDB

   A multi-model database that stores graphs, JSON documents, search and vector data, queried with one language called AQL.

   8.0overall

   A multi-model database that stores graphs, JSON documents, search and vector data, queried with one language called AQL.

   Best forTeams that want graph, document and vector data in one database

   Adoption data

   14.3kThe ArangoDB open-source repository on GitHub had 14.3k stars when we checked in November 2026.

   GitHub, arangodb/arangodb repository (2026): “14.3k stars”

   ArangoDB is the pick when a graph is only part of the data problem. It is a multi-model database: one engine stores JSON documents, graphs, full-text search, vectors and geospatial data, and AQL queries all of them in one statement. That means a knowledge graph can sit next to the documents it describes without a second database. Arango now sells it as part of a broader contextual data platform, with the Arango Managed Platform running clusters on AWS and Google Cloud, and Enterprise Edition adding replication, failover, hot backups, SmartGraphs and extended sharding. The GitHub repository had 14.3k stars when we checked. The licensing deserves attention: the pricing page says Community Edition is free for evaluation and non-commercial use, so commercial production needs a paid license, and USD prices are not published. Teams that only need a graph may find Neo4j or Memgraph simpler. We compared documented features and published prices.

   Strengths

   • +One engine replaces a separate document store, graph database and search index
   • +Single query language across data models
   • +Managed cluster option with high availability

   Limitations

   • −Community Edition is free only for evaluation and non-commercial use
   • −Replication, failover and hot backups require Enterprise Edition
   • −No published USD prices for Enterprise or the managed platform

   SummaryArangoDB is the best choice for teams that want graph, document and vector data in one engine because AQL queries all of them in a single language. Commercial production use needs Enterprise Edition or the managed platform.

6. 6

   TigerGraph

   A distributed graph analytics database for deep-link queries, sold as the managed Savanna service and as self-managed editions.

   8.0overall

   A distributed graph analytics database for deep-link queries, sold as the managed Savanna service and as self-managed editions.

   Best forEnterprises running deep multi-hop analytics on large graphs

   TigerGraph is built for analytics that follow many hops across a large graph, such as fraud scoring or supply chain impact analysis. It supports GSQL, its own language, alongside Cypher and GQL, and ships graph algorithm and AI/ML libraries plus hybrid graph and vector search. The managed Savanna service has a free trial with up to 32 vCPUs and 256 GB RAM per workspace, and the paid Savanna plan costs $45 per GB per month for 24/7 service in US and Tier 1 regions, scaling to 512 vCPUs and 4 TB of RAM per workspace with automatic backups. Business Critical adds multi-zone deployment and 99.95% uptime from $126 per GB per month, and instance rates are published by the hour, from $1.00 for TG-00. The free Community Edition runs on one server with up to 300 GB of graph and vector storage, which is generous for evaluation. The trade-off is cost at scale and GSQL's learning curve. We compared documented features and published prices.

   Strengths

   • +Free Community Edition up to 300 GB on a single server
   • +Published per-GB and per-hour rates, from $1.00 per hour for the TG-00 instance
   • +Scales to 4 TB RAM per workspace on Savanna

   Limitations

   • −$45 per GB per month adds up for large graphs
   • −GSQL is a proprietary language
   • −Business Critical rises to $126 per GB per month

   SummaryTigerGraph is the best choice for deep multi-hop analytics because Savanna scales to 4 TB of RAM per workspace and the free Community Edition handles up to 300 GB. Smaller teams will usually spend less on Neo4j or FalkorDB.

7. 7

   Graphwise GraphDB

   An RDF and SPARQL semantic graph database with built-in reasoning, sold as part of the Graphwise platform.

   7.9overall

   An RDF and SPARQL semantic graph database with built-in reasoning, sold as part of the Graphwise platform.

   Best forKnowledge graph teams that work with RDF, ontologies and reasoning

   GraphDB is a standards-based answer to the knowledge graph question. It stores RDF and is queried with SPARQL, the W3C standards used for ontologies, linked data and many public knowledge graphs. Its main feature is real-time forward-chaining reasoning: rules in an ontology produce inferred facts as data loads, so queries see relationships that were never written explicitly. The product page also lists native GraphRAG and LangChain integration for grounding LLM answers, high-availability clustering, and connectors for Kafka, MongoDB and Elasticsearch. GraphDB Free costs nothing and includes the Lucene connector but runs a single query at a time. GraphDB Enterprise removes that limit and adds the Elasticsearch, OpenSearch, Solr and Kafka connectors, at prices quoted on request. GraphDB now sits inside the Graphwise platform alongside taxonomy and text-mining tools. Teams without RDF experience may find a property graph such as Neo4j quicker to start with. We compared documented features and published prices.

   Strengths

   • +GraphDB Free costs nothing and includes the Lucene connector
   • +Reasoning engine infers new facts from ontologies
   • +Built for standards-based knowledge graphs

   Limitations

   • −GraphDB Free runs a single query at a time
   • −Enterprise prices are not published
   • −RDF and SPARQL take longer to learn than Cypher

   SummaryGraphwise GraphDB is the best choice for RDF knowledge graphs because it combines SPARQL with real-time forward-chaining reasoning and offers a free edition. Teams that need concurrent queries must budget for GraphDB Enterprise.

8. 8

   JanusGraph

   A Linux Foundation open-source graph database that runs Gremlin on top of storage backends such as Cassandra, HBase and Bigtable.

   7.9overall

   A Linux Foundation open-source graph database that runs Gremlin on top of storage backends such as Cassandra, HBase and Bigtable.

   Best forTeams that want a free, Apache 2.0 graph on their own Cassandra or HBase cluster

   Adoption data

   5.9kThe JanusGraph repository on GitHub had 5.9k stars when we checked in November 2026.

   GitHub, JanusGraph/janusgraph repository (2026): “5.9k stars”

   JanusGraph is the free route to a large distributed graph. The project describes itself as optimized for graphs with hundreds of billions of vertices and edges spread across a multi-machine cluster, transactional, able to serve thousands of concurrent users in real time, and fully open source under the Apache 2.0 license. It is a Linux Foundation project, which means no vendor can change the license. JanusGraph does not store data itself: it runs on top of Cassandra, HBase or Bigtable, and uses Elasticsearch or Solr for indexing, so it fits teams that already operate those systems. Queries use Apache TinkerPop Gremlin. The trade-off is operations: there is no managed service or paid support from the project, and you run every layer yourself. The GitHub repository had 5.9k stars when we checked. Teams that want Cypher or a managed service should pick Neo4j or Amazon Neptune. We compared documented features and published prices.

   Strengths

   • +Free under Apache 2.0 with no paid tier
   • +Hosted by the Linux Foundation, so no single vendor controls it
   • +Reuses storage clusters many teams already run

   Limitations

   • −No managed service or vendor support from the project
   • −You operate the storage and index backends yourself
   • −Gremlin only, no Cypher or SPARQL

   SummaryJanusGraph is the best free graph database for teams that already run Cassandra or HBase because it is Apache 2.0 licensed and scales across a cluster. Teams without operations staff should choose a managed service instead.

9. 9

   Memgraph

   An in-memory graph database queried with Cypher, built for real-time streaming and analytics workloads.

   7.8overall

   An in-memory graph database queried with Cypher, built for real-time streaming and analytics workloads.

   Best forTeams that need real-time graph queries on streaming data

   Adoption data

   4.7kThe Memgraph repository on GitHub had 4.7k stars when we checked in November 2026.

   GitHub, memgraph/memgraph repository (2026): “4.7k stars”

   Memgraph keeps the whole graph in memory, which suits workloads that need answers while data is still arriving. It speaks Cypher, so teams coming from Neo4j can reuse queries, and its docs include migration guides for that move. The free Community Edition already includes ACID transactions with on-disk persistence, high-availability replication, vector search, the MAGE algorithm library and stream connectors for Kafka, Pulsar and Redpanda. Enterprise adds role-based and label-based access control, SSO, multi-tenancy, automatic failover and audit logging, and Memgraph says it is priced on memory capacity only, with no per-query, compute or replica fees, though the figures are quoted on request. Memgraph Cloud offers a free trial on AWS across 6 regions with instances from 1 GB to 32 GB of RAM. The limit is the model itself: graphs must fit in memory, and the GitHub repository's 4.7k stars point to a smaller community than Neo4j's. We compared documented features and published prices.

   Strengths

   • +Free Community Edition includes high-availability replication and vector search
   • +Enterprise is priced on memory only, with no per-query, compute or replica charges
   • +Streams from Kafka, Pulsar and Redpanda without extra ETL

   Limitations

   • −Graph size is bounded by available RAM
   • −Enterprise prices are not published
   • −Memgraph Cloud runs only on AWS

   SummaryMemgraph is the best choice for real-time graph analytics on streaming data because it keeps the graph in memory and reads from Kafka, Pulsar and Redpanda. Graphs larger than available RAM fit better in NebulaGraph or TigerGraph.

10. 10

    Stardog

    An enterprise knowledge graph platform with a graph database, virtual graphs over existing sources and an inference engine.

    7.6overall

    An enterprise knowledge graph platform with a graph database, virtual graphs over existing sources and an inference engine.

    Best forEnterprises that want a knowledge graph over data left in place

    Stardog is aimed at enterprises that want a knowledge graph across data they cannot or will not move. Its virtual graph feature maps existing databases and lakes into the graph and queries them in place, and its inference engine reasons over ontologies to add implied facts. The platform bundles Designer for modeling, Explorer for browsing, Studio for SPARQL and path queries, and Voicebox for asking questions in plain language. Stardog Free can be used without commercial limitations, according to the pricing page, while high availability, caching, backups, LDAP integration and the full set of connectors require Stardog Enterprise, which comes with a dedicated customer success contact and is priced on request. It runs on premises, in Stardog Cloud or through cloud marketplaces. The trade-off is cost visibility and a smaller community; for a self-contained RDF store with a free edition, GraphDB is a lighter start. We compared documented features and published prices.

    Strengths

    • +Stardog Free has no commercial-use limitation, per the pricing page
    • +Virtual graphs avoid moving data out of source systems
    • +Designer, Explorer and Studio tools cover modeling to querying

    Limitations

    • −High availability, caching, backups and LDAP need Stardog Enterprise
    • −Enterprise prices are not published
    • −Smaller developer community than property graph databases

    SummaryStardog is the best choice for enterprises that want a knowledge graph over data left in source systems because virtual graphs query those systems in place. Teams that only need a standalone graph will spend less elsewhere.

Questions or corrections: editorial@statlyst.com · Disclosure