What is Blazegraph?
It is a fully open-source high-performance graph database supporting the RDF data model and RDR. It operates as an embedded database or over a client/server REST API.
Blazegraph is a tool in the Graph Databases category of a tech stack.
Blazegraph is an open source tool with GitHub stars and GitHub forks. Here’s a link to Blazegraph's open source repository on GitHub
Who uses Blazegraph?
3 companies reportedly use Blazegraph in their tech stacks, including Zero Technologies, Nelson.ai, and Industrial Inference.
GrapheneDB, Linkurious, Cartography, Structr, and Graph Story are some of the popular tools that integrate with Blazegraph. Here's a list of all 5 tools that integrate with Blazegraph.
Pros of Blazegraph
Support for SPARQL
Easy Setup and Use
Support for RDF
- High Performance Native graph database
- Blueprints API or RDF/SPARQL
- Single machine data storage to ~50B triples/quads (RWStore)
- REST API with embedded and/or webapp deployment (NanoSparqlServer)
- Fast 100% native SPARQL 1.1 evaluation
- Fast RDFS+ inference and truth maintenance
- Triples, quads, or Reification Done Right (RDR) support
- 100% Java memory manager leverages the JVM native heap (no GC)
- Vertex-centric API
Blazegraph Alternatives & Comparisons
What are some alternatives to Blazegraph?
See all alternatives
Neo4j stores data in nodes connected by directed, typed relationships with properties on both, also known as a Property Graph. It is a high performance graph store with all the features expected of a mature and robust database, like a friendly query language and ACID transactions.
It 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. It is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time.
It is an open source NoSQL database management system written in Java. It is a Multi-model database, supporting graph, document, key/value, and object models, but the relationships are managed as in graph databases with direct connections between records.
Dgraph's goal is to provide Google production level scale and throughput, with low enough latency to be serving real time user queries, over terabytes of structured data. Dgraph supports GraphQL-like query syntax, and responds in JSON and Protocol Buffers over GRPC and HTTP.
Titan 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. Titan is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time.