10 Best Open Source Graph Databases - PiracyData.org (2023)

Introduction

Open source is always a hot topic among developers including software development outsourcing companies, and for good reason. Not only does it offer an alternative to costly proprietary software, but it also allows developers to peek under the hood and see how things work.

In this blog post, we’ll take a look at 10 of the best open source graph databases. Each has its own unique features and benefits, so read on to find out which one is right for you!

1. Neo4j Community Edition

Neo4j Community Edition is an open source graph database, licensed and distributed under GPL v3. It is a high performance graph db that supports Linux, Mac and Windows. This database is a perfect choice for managing data relationships. It’s a great tool for powering business applications and data-driven projects.

If for example you are working on an application project that has access to a Neo4j database running with organizational devices or even personal devices, then it is free to use the Community Edition whether or not the application is closed source.

Please note that Neo4j has a commercial version or what is commonly referred to as the Enterprise Edition. This is understandable because at the end of the day the creators need to find a way to power these resources. And so the commercial edition provides the resources to continue providing the amazing product.

The good part is that for a limited number of users, the commercial edition is available at no cost. Startups with a staff count of less than 50 can contact Neo4j and request a free Startup License. Single users can also get a free license for development work.

2. ArangoDB

ArangoDB offers a comprehensive, powerful, and intuitive graph database solution that is perfect for managing complex data landscapes. It’s a multi-model database that is easy to use, and scalable, making it the perfect choice for any business or organization in need of a robust graph database solution.

It has tons of great features that make it one of the best graph db available, including:

• A powerful and intuitive query language that makes it easy to find the information you need, fast.
• The ability to handle very large graphs without running into performance issues.
• The ability to scale up easily to meet increased demand.
• Supports graph, document and search.
• Optimum flexibility as all data models & access patterns that are supported can be combined in queries.
• User-friendly interface.
• A unique storage model that makes it perfect for storing and querying data in graphs.
• Can handle large graphs with ease, making it a great choice for data-intensive applications.
• Its scalability means that it can handle even the largest data sets with ease.
• It’s easy to use, making it a great choice for developers who want to get up and running quickly.

3. Apache TinkerPop

Apache TinkerPop is an open source graph database that is released under the Apache License. It provides a set of interfaces and implementations for a graph database that can be used by application developers to create, read, update, and delete data in a graph database.

The Apache Tinkerpop™ framework can be used to store both graphs and analytical data. It’s an easy way for businesses, such as those in the financial or travel industry, who want to access their information on any device at any time without having to worry about losing some critical piece of information.

This graph uses the Gremlin query language. The Gremlin language is a functional, data-flow text that enables users to concisely express complex traversals of a property graph.

TinkerPop offers official language drivers for Java, Groovy, Python, .NET, and NodeJS, plus additional language drivers from the community.

Key features

• TinkerPop is designed to be scalable, which means it can handle large amounts of data without issues.
• TinkerPop is fast and efficient, so you get results in no time.
• TinkerPop is flexible and customizable, so tailor it to your specific needs.

4. Nebula Graph

Nebula Graph is quickly becoming one of the most popular open source graph database thanks to its impressive features and ease of use. Whether you’re looking to store complex data or simply need a fast and reliable database, Nebula Graph is the perfect solution.

One of the most outstanding aspects about Nebula Graph is that it is properly built for the cloud. This means it offers some of the best in class features.

Here are the impressive features of the Nebula Graph:

• High performance: Nebula Graph uses the powerful storage engine RocksDB to provide fast read and write performance with high throughput. It also has a state-of-the art design that delivers highly concurrent access, allowing it to process graphs containing trillions of edges or vertices without issue!
• Horizontal scalability: Nebula Graph offers scalability thanks to the shared-nothing distributed architecture that it uses. This means the performance of the cluster will not be affected whenever new nodes or services are added.
• Compatible with openCypher: The nGQL query language of Nebula Graph is gradually being incorporated into openCypher. As a result, openCypher users can easily start using Nebula Graph with no learning curve.
• Stability: Nebula Graph offers unparalleled stability, always ready to be deployed in the most demanding production ecosystems.This has been validated by the long list of large companies that are already using it in real-world environments. Some of the companies that trust the Nebula Graph include Tencent, WeBank, and Meituan.

This graph is best suited for DevOps & DBA, data architects and scientists. It integrates very well with other open source big data frameworks like Spark GraphX, and Flink among others.

5. Dgraph

Dgraph is an open source graph database that is unrivaled in terms of speed, scalability, and features. It is designed to be horizontally scalable, so it can easily handle large amounts of data.

Dgraph also has a number of unique features that make it stand out from other graph databases. For example, Dgraph supports real-time search and analytics, so you can instantly find the information you need. Additionally, Dgraph is highly customizable, so you can tailor it to your specific needs.

Key features

• Supports Native GraphQL.
• Scales horizontally and vertically without affecting uptime.
• Supports Distributed ACID Transactions (Jepsen tested).
• Two Jepsen tests have been completed successfully.
• Supports multiple language drivers including Java, JavaScript, Go, Python, C#.
• Provides an SQL migration tool.
• All database files are encrypted at rest using keys that are supplied by the user.

There’s a huge amount of documentation and support available, and the developer community is always working on new features and improvements.

6. Memgraph

Memgraph is a powerful open source graph database that can handle massive amounts of data. It’s perfect for companies that need to manage complex data relationships, and offers a lot of flexibility and scalability.

Developers can build cool data-driven stuff with Memgraph such as recommendation engines, e-commerce platforms or fraud detection systems. It offers a PageRank algorithm which developers can use to create social network features to measure the value of nodes based on incoming relationships and how valuable the source node is.

What makes Memgraph particularly interesting is that it’s designed to work with big data sets. That means businesses and organizations of all sizes can take advantage of its capabilities, and they don’t have to worry about licensing fees or restrictions.

Some of the popular use case for Memgraph include;

• Fraud Detection
• Social Network Analysis
• Route Computation
• Identity and Access Management
• Process Optimisation
• Recommendation Engines

7. OrientDB Community Edition

The OrientDB Community Edition is the open source version of OrientDB, a very powerful open source graph database. It’s written in Java and runs on Windows, Mac, and Linux. It has an index-free search algorithm, which makes finding information a breeze. Plus, it has a replication feature that ensures your data is always safe.

OrientDB also boasts an impressive performance, making it the perfect choice for high-volume applications. And if that’s not enough, it also has an intuitive user interface that makes it easy to get started.

More features:

• Offers both ACID and BASE guarantees, so you can be sure your data is safe and reliable
• Powerful search engine that makes finding specific information quick and easy.
• Supports clustering, so you can easily scale your database as your needs grow.
• A rich set of APIs that make it easy to integrate with your existing systems.

It’s important to note that OrientDB combines the power of graphs and document scalability to deliver high performance. It’s the first Multi-Model Open Source NoSQL DBMS that has been able to achieve this.

8. HypergraphDB

HypergraphDB is one of the most popular graph databases because it offers a lot of features and benefits that other graph databases don’t. Its storage mechanism is based on the directed hypergraphs mechanism, a high performance knowledge management formalism. This graph is most suited for knowledge management, AI and projects that are focussed on the semantic web. It can also be used for all sizes of Java projects as an object-oriented database.

HypergraphDB has a powerful query engine that lets you run complex queries in a fraction of the time it would take with other databases. The user interface is intuitive, making it easy to manage data.

Here are the standout features that elevate HypergraphDB to this list of the very best graph databases:

• Powerful data modeling and knowledge representation.
• Customizable indexing and storage management.
• An extendable, dynamic DB schema that accommodates custom typing.
• Java OO database.
• MVCC/STM: fully transactional and multi-threaded. Concurrent writes and reads don’t create blocking problems!
• Efficient data distribution thanks to a P2P framework.

9. Cayley

The creators of Cayley say that this open source graph was inspired by the graph databases behind Freebase as well as the knowledge graph by Google. There you have it! And indeed the inspiration must be doing magic because they have built a rich graph with lots of easy to use features. It’s available under Apache 2.0 license, free to use for any kind of projects.

Being highly modular means it can handle large graph datasets with ease, making it the perfect choice for companies that need to store and query complex data sets. And if you’re already familiar with popular programming languages like Python and JavaScript, you’ll be happy to know that Cayley supports multiple query languages.

These are some of the characteristics that make Cayley an outstanding graph db:

• Excellent for linked data: Supports RDF databases, including data formats that are multiple linked such as NQuads and JSON-LD.
• Query languages: Supports multiple query languages including Gizmo (Gremlin dialect), MQL and GraphQL dialect
• Integration with existing databases: Cayley works perfectly on top of existing databases regardless of the data model that is used.
• Modularity: Everything in Cayley is modular, meaning you can extend it with whatever you want including new formats, query languages, or custom models.
• Community driven: This is perhaps the most valuable feature of this graph. A community is very important in open source databases and Cayley boasts an active community that shares a passion for linked data.

10. RedisGraph

RedisGraph is a new addition to the Redis family of databases that offers powerful capabilities for storing and manipulating graph data. It is different from other graph databases in that it is built on top of Redis, which gives it some significant advantages. Chief among these is the speed; RedisGraph is incredibly fast, making it an excellent choice for real-time applications. The support for traversals is up there, which is a key requirement for graph databases.

Check out these powerful feature of RedisGraph:

• RedisGraph offers quick indexing and querying.
• The data structures are memory efficient and allow customization.
• Supports the openCypher query language, one of the most popular graph query languages for graphs.
• On-disk persistence, which means that your data will be safe even if there is a power outage or other similar problems.
• Tabular result sets:

RedisGraph is licensed under the Redis License Agreement. It’s a young project but still a competent alternative to many existing databases.

Concluding remarks

Graph databases are becoming more and more popular every day. As this technology grows, the community around it is evidently growing with it. This is good news because it means that newcomers can look forward to an active and supportive community.

And so if you’re looking for a graph database that has an active and helpful community, remember these top graph databases. All these options have great communities that will be happy to help you get started.