Alternatives to JanusGraph

Compare JanusGraph alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to JanusGraph in 2025. Compare features, ratings, user reviews, pricing, and more from JanusGraph competitors and alternatives in order to make an informed decision for your business.

  • 1
    Redis

    Redis

    Redis Labs

    Redis Labs: home of Redis. Redis Enterprise is the best version of Redis. Go beyond cache; try Redis Enterprise free in the cloud using NoSQL & data caching with the world’s fastest in-memory database. Run Redis at scale, enterprise grade resiliency, massive scalability, ease of management, and operational simplicity. DevOps love Redis in the Cloud. Developers can access enhanced data structures, a variety of modules, and rapid innovation with faster time to market. CIOs love the confidence of working with 99.999% uptime best in class security and expert support from the creators of Redis. Implement relational databases, active-active, geo-distribution, built in conflict distribution for simple and complex data types, & reads/writes in multiple geo regions to the same data set. Redis Enterprise offers flexible deployment options, cloud on-prem, & hybrid. Redis Labs: home of Redis. Redis JSON, Redis Java, Python Redis, Redis on Kubernetes & Redis gui best practices.
  • 2
    RavenDB

    RavenDB

    RavenDB

    RavenDB is the pioneer NoSQL Document Database that is fully transactional (ACID) across your database and throughout your cluster. At a fraction of the total cost of ownership (TCO), our open source distributed database offers high availability and high performance with zero administration. It is designed as an easy to use all-in-one database which minimizes the need for third party addons, tools, or support to boost developer productivity and get your project into production fast. You can setup and secure a data cluster in minutes and deploy in the cloud, on-premise or in a hybrid environment. RavenDB offers a Database as a Service solution, allowing you to pass on all your database operations to us so you can focus exclusively on your application. RavenDB has a built-in storage engine, Voron, that operates at speeds up to 1 million reads per second and 150,000 writes per second on a single node using simple commodity hardware to increase your application’s performance.
  • 3
    OrientDB
    OrientDB is the world’s fastest graph database. Period. An independent benchmark study by IBM and the Tokyo Institute of Technology showed that OrientDB is 10x faster than Neo4j on graph operations among all the workloads. Drive competitive advantage and accelerate innovation with new revenue streams.
  • 4
    Cayley

    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).
  • 5
    Apache Cassandra

    Apache Cassandra

    Apache Software Foundation

    The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance. Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data. Cassandra's support for replicating across multiple datacenters is best-in-class, providing lower latency for your users and the peace of mind of knowing that you can survive regional outages.
  • 6
    Nebula Graph
    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.
  • 7
    TigerGraph

    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.
  • 8
    Fauna

    Fauna

    Fauna

    Fauna is a data API for modern applications that facilitates rich clients with serverless backends by providing a web-native interface with support for GraphQL and custom business logic, frictionless integration with the serverless ecosystem, a no compromise multi-cloud architecture you can trust and grow with and total freedom from database operations. Instantly create multiple databases in one account leveraging multi-tenancy for development or customer-facing use case. Create a distributed database across one geography or the globe in just three clicks and easily import existing data. Scale seamlessly without ever managing servers, clusters, data partitioning, or replication. Track usage and consumption-based billing in near real time via a dashboard.
  • 9
    HugeGraph

    HugeGraph

    HugeGraph

    HugeGraph is a fast-speed and highly-scalable graph database. Billions of vertices and edges can be easily stored into and queried from HugeGraph due to its excellent OLTP ability. As compliance to Apache TinkerPop 3 framework, various complicated graph queries can be accomplished through Gremlin (a powerful graph traversal language). Among its features, it provides compliance to Apache TinkerPop 3, supporting Gremlin. Schema Metadata Management, including VertexLabel, EdgeLabel, PropertyKey and IndexLabel. Multi-type Indexes, supporting exact query, range query and complex conditions combination query. Plug-in Backend Store Driver Framework, supporting RocksDB, Cassandra, ScyllaDB, HBase and MySQL now and easy to add other backend store driver if needed. Integration with Hadoop/Spark. HugeGraph relies on the TinkerPop framework, we refer to the storage structure of Titan and the schema definition of DataStax.
  • 10
    TIBCO Graph Database
    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.
  • 11
    Oceanbase

    Oceanbase

    Oceanbase

    OceanBase eliminates the complexity of traditional sharding databases, enabling you to effortlessly scale your database to meet ever-growing workloads, whether horizontally, vertically, or even at the tenant level. This facilitates on-the-fly scaling and linear performance growth without downtime or necessitating changes to applications in high-concurrency scenarios, ensuring quicker and more reliable responses to performance-intensive critical workloads. Empower mission-critical workloads and performance-intensive applications across both OLTP and OLAP scenarios, all while maintaining full compatibility with MySQL. 100% ACID Compliance, natively supports distributed transactions with multi-replica strong synchronization built upon Paxos protocols. Experience ultimate query performance that your mission-critical and time-sensitive workloads can depend on. This effectively eliminates downtime, and ensures your mission-critical workload remains always available.
  • 12
    Blazegraph

    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.
  • 13
    Azure Cosmos DB
    Azure Cosmos DB is a fully managed NoSQL database service for modern app development with guaranteed single-digit millisecond response times and 99.999-percent availability backed by SLAs, automatic and instant scalability, and open source APIs for MongoDB and Cassandra. Enjoy fast writes and reads anywhere in the world with turnkey multi-master global distribution. Reduce time to insight by running near-real time analytics and AI on the operational data within your Azure Cosmos DB NoSQL database. Azure Synapse Link for Azure Cosmos DB seamlessly integrates with Azure Synapse Analytics without data movement or diminishing the performance of your operational data store.
  • 14
    AllegroGraph

    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.
  • 15
    Neo4j

    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.
  • 16
    ArangoDB

    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.
  • 17
    Apache TinkerPop

    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).
  • 18
    Apache Trafodion

    Apache Trafodion

    Apache Software Foundation

    Apache Trafodion is a webscale SQL-on-Hadoop solution enabling transactional or operational workloads on Apache Hadoop. Trafodion builds on the scalability, elasticity, and flexibility of Hadoop. Trafodion extends Hadoop to provide guaranteed transactional integrity, enabling new kinds of big data applications to run on Hadoop. Full-functioned ANSI SQL language support. JDBC/ODBC connectivity for Linux/Windows clients. Distributed ACID transaction protection across multiple statements, tables, and rows. Performance improvements for OLTP workloads with compile-time and run-time optimizations. Support for large data sets using a parallel-aware query optimizer. Reuse existing SQL skills and improve developer productivity. Distributed ACID transactions guarantee data consistency across multiple rows and tables. Interoperability with existing tools and applications. Hadoop and Linux distribution neutral. Easy to add to your existing Hadoop infrastructure.
  • 19
    Dgraph

    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.
  • 20
    Grakn

    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.
  • 21
    InfiniteGraph

    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.
  • 22
    Amazon Neptune
    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.
  • 23
    FalkorDB

    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.
  • 24
    Fluree

    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.
  • 25
    DataStax

    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.
  • 26
    Apache Geode
    Build high-speed, data-intensive applications that elastically meet performance requirements at any scale. Take advantage of Apache Geode's unique technology that blends advanced techniques for data replication, partitioning and distributed processing. Apache Geode provides a database-like consistency model, reliable transaction processing and a shared-nothing architecture to maintain very low latency performance with high concurrency processing. Data can easily be partitioned (sharded) or replicated between nodes allowing performance to scale as needed. Durability is ensured through redundant in-memory copies and disk-based persistence. Super fast write-ahead-logging (WAL) persistence with a shared-nothing architecture that is optimized for fast parallel recovery of nodes or an entire cluster.
  • 27
    PuppyGraph

    PuppyGraph

    PuppyGraph

    PuppyGraph empowers you to seamlessly query one or multiple data stores as a unified graph model. Graph databases are expensive, take months to set up, and need a dedicated team. Traditional graph databases can take hours to run multi-hop queries and struggle beyond 100GB of data. A separate graph database complicates your architecture with brittle ETLs and inflates your total cost of ownership (TCO). Connect to any data source anywhere. Cross-cloud and cross-region graph analytics. No complex ETLs or data replication is required. PuppyGraph enables you to query your data as a graph by directly connecting to your data warehouses and lakes. This eliminates the need to build and maintain time-consuming ETL pipelines needed with a traditional graph database setup. No more waiting for data and failed ETL processes. PuppyGraph eradicates graph scalability issues by separating computation and storage.
  • 28
    AnzoGraph DB

    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.
  • 29
    ClickHouse

    ClickHouse

    ClickHouse

    ClickHouse is a fast open-source OLAP database management system. It is column-oriented and allows to generate analytical reports using SQL queries in real-time. ClickHouse's performance exceeds comparable column-oriented database management systems currently available on the market. It processes hundreds of millions to more than a billion rows and tens of gigabytes of data per single server per second. ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency. ClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure.
  • 30
    FoundationDB

    FoundationDB

    FoundationDB

    FoundationDB is multi-model, meaning you can store many types data in a single database. All data is safely stored, distributed, and replicated in the Key-Value Store component. FoundationDB is easy to install, grow, and manage. It has a distributed architecture that gracefully scales out, and handles faults while acting like a single ACID database. FoundationDB provides amazing performance on commodity hardware, allowing you to support very heavy loads at low cost. FoundationDB has been running in production for years and been hardened with lessons learned. Backing FoundationDB up is an unmatched testing system based on a deterministic simulation engine. We encourage your participation in our open-source community! Join us in technical and user discussions on the community forums, and learn how to contribute.
  • 31
    ArcadeDB

    ArcadeDB

    ArcadeDB

    Manage complex models using ArcadeDB without any compromise. Forget about Polyglot Persistence. no need for multiple databases. You can store graphs, documents, key values and time series all in one ArcadeDB Multi-Model database. Since each model is native to the database engine, you don't have to worry about translations slowing you down. ArcadeDB's engine was built with Alien Technology. It's able to crunch millions of records per second. With ArcadeDB, the traversing speed is not affected by the database size. It is always constant, whether your database has a few records or billions. ArcadeDB can work as an embedded database, on a single server and can scale up using multiple servers with Kubernetes. Flexible enough to run on any platform with a small footprint. Your data is secure. Our unbreakable fully transactional engine assures durability for mission-critical production databases. ArcadeDB uses a Raft Consensus Algorithm to maintain consistency across multiple servers.
  • 32
    TiDB

    TiDB

    PingCAP

    An open-source, cloud-native, distributed SQL database for elastic scale and real-time analytics. Supported by a wealth of open-source data migration tools in the ecosystem, TiDB gives you the freedom to choose your own vendor and avoid lock-in. Purposely built to deliver SQL at scale, TiDB eliminates the scaling problems of traditional relational databases without intrusion to your application. HTAP database platform that enables real-time situation awareness and decision making on live transactional data and eliminates friction between IT and business goals. TiDB is ACID-compliant and strongly consistent. You can use TiDB as a scale-out MySQL database with familiar SQL syntaxes and ecosystem tools. TiDB automatically shards your data so you don’t have to do it manually. You can simply add new nodes to scale horizontally and elastically to meet your business growth. TiDB simplifies the ETL process and automatically recovers from errors.
  • 33
    SingleStore

    SingleStore

    SingleStore

    SingleStore (formerly MemSQL) is a distributed, highly-scalable SQL database that can run anywhere. We deliver maximum performance for transactional and analytical workloads with familiar relational models. SingleStore is a scalable SQL database that ingests data continuously to perform operational analytics for the front lines of your business. Ingest millions of events per second with ACID transactions while simultaneously analyzing billions of rows of data in relational SQL, JSON, geospatial, and full-text search formats. SingleStore delivers ultimate data ingestion performance at scale and supports built in batch loading and real time data pipelines. SingleStore lets you achieve ultra fast query response across both live and historical data using familiar ANSI SQL. Perform ad hoc analysis with business intelligence tools, run machine learning algorithms for real-time scoring, perform geoanalytic queries in real time.
    Starting Price: $0.69 per hour
  • 34
    AntDB

    AntDB

    Antdb AsiaInfo

    AntDB is a cloud-native, distributed relational database developed by AsiaInfo Technologies, designed to handle high-performance online transaction processing and online analytical processing workloads. AntDB has been serving over 1 billion subscribers across 24 provinces in China, supporting massive business data related to calls, internet access, payments, and billing. AntDB's cloud-native distributed architecture supports online scalability, data consistency, and high availability across data centers. It is compatible with SQL2016 standards and integrates seamlessly with various domestic ecosystems, including mainstream CPUs and operating systems. The platform offers features such as automatic high availability, online elastic capacity expansion, and read/write splitting at the kernel level to efficiently manage traffic loads during peak periods. AntDB has been successfully commercialized in industries like telecommunications, finance, transportation, and energy.
  • 35
    KgBase

    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
  • 36
    Apache Giraph

    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.
  • 37
    RushDB

    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-Ready
    Starting Price: $9/month
  • 38
    Objectivity/DB

    Objectivity/DB

    Objectivity, Inc.

    Objectivity/DB is a massively scalable, high performance, distributed Object Database (ODBMS). It is extremely good at handling complex data, where there are many types of connections between objects and many variants. Objectivity/DB can also serve as a massively scalable, high performance graph database. Its DO query language supports standard data retrieval queries as well as high-performance path-based navigational queries. Objectivity/DB is a distributed database, presenting a Single Logical View of its managed data. Data can be hosted on a single machine or distributed across up to 65,000 machines. Connected items can span machines. Objectivity/DB runs on 32 or 64-bit processors running Windows, Linux, and Mac OS X. APIs include: C++, C#, Java and Python. All platform and language combinations are interoperable. For example, objects stored by a program using C++ on Linux can be read by a C# program on Windows and a Java program on Mac OS X.
    Starting Price: See Pricing Details...
  • 39
    rqlite

    rqlite

    rqlite

    The lightweight, user-friendly, distributed relational database built on SQLite. Fault tolerance and high availability with zero hassle. rqlite is a distributed relational database that combines the simplicity of SQLite with the robustness of a fault-tolerant, highly available system. It's developer-friendly, its operation is straightforward, and it's designed for reliability with minimal complexity. Deploy in seconds, with no complex configurations. Seamlessly integrates with modern cloud infrastructures. Built on SQLite, the world’s most popular database. Supports full-text search, Vector Search, and JSON documents. Access controls and encryption for secure deployments. Rigorous, automated testing ensures high quality. Clustering provides high availability and fault tolerance. Automatic node discovery simplifies clustering.
  • 40
    TiDB Cloud

    TiDB Cloud

    PingCAP

    A cloud-native distributed HTAP database built for elastic scaling and real-time analytics in a fully managed service, with its serverless tier enabling your launching of the HTAP database in seconds. Elastically and transparently scale to hundreds of nodes for critical workloads without changing business logic. Use what you know about SQL, and maintain your relational model and global ACID transactions while coping with your hybrid workloads at ease. Equipped with a built-in high-performance analytics engine to analyze operational data without using an ETL. Scale-out to hundreds of nodes while maintaining ACID transactions. No need to bother with sharding or facing downtime. Ensure data accuracy at scale, even for simultaneous updates to the same data source. Increase productivity and shorten time-to-market for your applications with TiDB’s MySQL compatibility. Easily migrate data from existing MySQL instances without the need to rewrite code.
    Starting Price: $0.95 per hour
  • 41
    Couchbase

    Couchbase

    Couchbase

    Unlike other NoSQL databases, Couchbase provides an enterprise-class, multicloud to edge database that offers the robust capabilities required for business-critical applications on a highly scalable and available platform. As a distributed cloud-native database, Couchbase runs in modern dynamic environments and on any cloud, either customer-managed or fully managed as-a-service. Couchbase is built on open standards, combining the best of NoSQL with the power and familiarity of SQL, to simplify the transition from mainframe and relational databases. Couchbase Server is a multipurpose, distributed database that fuses the strengths of relational databases such as SQL and ACID transactions with JSON’s versatility, with a foundation that is extremely fast and scalable. It’s used across industries for things like user profiles, dynamic product catalogs, GenAI apps, vector search, high-speed caching, and much more.
  • 42
    NuoDB

    NuoDB

    NuoDB

    The world is moving to distributed applications and architectures, and your database should too. Learn how you can deploy where you want, when you want, and how you want with a distributed SQL database. Migrate existing SQL applications to a distributed, multi-node architecture that can dynamically scale out and in. Our Transaction Engines (TEs) and Storage Managers (SMs) work together to ensure ACID compliance across multiple nodes. Deploy in a distributed architecture. When you deploy your database with multiple nodes, the loss of one or multiple nodes will not result in the loss of database access. Deploy TEs and SMs to meet your variable workload needs, or deploy in the different environments the teams in your organization uses: in private and public clouds, in hybrid environments, and across clouds.
  • 43
    Yugabyte

    Yugabyte

    Yugabyte

    The Leading High-Performance Distributed SQL Database. Open source, cloud native relational DB for powering global, internet-scale apps. Single-Digit Millisecond Latency Build blazing fast cloud applications by serving queries directly from the DB. Massive Scale. Achieve millions of transactions per second and store multiple TB’s of data per node. Geo-Distribution. Deploy across regions and clouds with synchronous or multi-master replication. Built for Cloud Native Architectures. Develop, deploy and operationalize modern applications faster than ever before with YugabyteDB. Gain Developer Agility. Leverage full power of PostgreSQL-compatible SQL and distributed ACID transactions. Operate Resilient Services. Ensure continuous availability even when underlying compute, storage or network fails. Scale On-Demand. Add and remove nodes at will. Say no to over-provisioned clusters forever. Lower User Latency.
  • 44
    Memstate

    Memstate

    Memstate

    Build high quality, mission critical applications with real-time performance at a fraction of the time and cost. Memstate is a new. Moving data back and forth between disk and RAM is not just extremely inefficient, it requires multiple layers of complex software that can be eliminated entirely. Use Memstate to structure and manage your data in-memory, obtain transparent persistence, concurrency control and transactions with strong ACID guarantees. note: this is too techy... Make your applications 100x faster, and your developers 10x more productive. Memstate has many possible use cases but is designed primarily to handle complex OLTP workloads in a typical enterprise application. In-memory operations are orders of magnitude faster than disk operations. A single Memstate engine can execute millions of read transactions and tens of thousands of write transactions per second, all at submillisecond latency.
    Starting Price: €200 per GB RAM per server
  • 45
    GraphBase

    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.
  • 46
    HCL OneDB

    HCL OneDB

    HCL Software

    Build and run distributed, database-driven enterprise applications with the highest levels of availability, scalability, and performance completely cloud native. For enterprises just starting their cloud native journey or those already executing a multi-cloud strategy, OneDB offers the flexibility, reliability, and ease-of-use needed to meet your application needs. Capturing the value of data for insight and actionable intelligence is made easier through fully automated database administration. You can drastically reduce the need for deep technical expertise to launch new ideas and still stay ahead of the competition. OneDB is great for application development. From broad support of interfaces and APIs to extensive programming language support, developers will find everything they need with OneDB. HCL offers the most versatile cloud native database in the market.
  • 47
    Oracle Spatial and Graph
    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.
  • 48
    GraphDB

    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).
  • 49
    Memgraph

    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.
  • 50
    RecallGraph

    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.