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Blazegraph vs Neo4j: What are the differences?

Introduction

Blazegraph and Neo4j are two popular graph databases that offer efficient storage and retrieval of connected data. While both databases serve similar purposes, there are several key differences between them.

  1. Data Model: Blazegraph utilizes a property graph model where data is represented as nodes and relationships with properties, similar to Neo4j. However, Neo4j additionally supports a labeled property graph model, allowing nodes and relationships to be grouped into labels or types.

  2. Query Language: Blazegraph supports SPARQL, a widely-used query language for RDF databases, allowing users to query and manipulate graph data using a structured query language. In contrast, Neo4j uses Cypher, a declarative query language that simplifies graph querying by providing a more user-friendly syntax.

  3. Scalability: Blazegraph is known for its scalability and performance in handling large-scale datasets. It offers horizontal scaling through sharding, allowing data to be distributed across multiple nodes for improved performance. On the other hand, while Neo4j also supports scaling, it is primarily designed for smaller to medium-sized datasets.

  4. Community and Ecosystem: Neo4j has a larger and more active community compared to Blazegraph. This translates to a wider range of available resources, including libraries, plugins, and community support. Neo4j's ecosystem is more mature and offers a broader selection of tools and integrations.

  5. Commercial Support: Neo4j has a well-established commercial support offering, which includes enterprise-grade features, professional services, and dedicated technical support. Blazegraph, on the other hand, primarily relies on community support and does not have a comparable commercial offering.

  6. Licensing: Blazegraph is available under an open-source GNU Affero General Public License (AGPL), allowing users to freely use, modify, and distribute the software. Neo4j, however, is available under a dual licensing model, where a community edition is free to use under the GPLv3 license, while commercial editions require a paid license.

In Summary, Blazegraph and Neo4j differ in their data model, query language, scalability, community support, commercial offerings, and licensing.

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Pros of Blazegraph
Pros of Neo4j
  • 1
    Support for SPARQL
  • 1
    Easy Setup and Use
  • 1
    Support for RDF
  • 70
    Cypher – graph query language
  • 61
    Great graphdb
  • 33
    Open source
  • 31
    Rest api
  • 27
    High-Performance Native API
  • 23
    ACID
  • 21
    Easy setup
  • 17
    Great support
  • 11
    Clustering
  • 9
    Hot Backups
  • 8
    Great Web Admin UI
  • 7
    Powerful, flexible data model
  • 7
    Mature
  • 6
    Embeddable
  • 5
    Easy to Use and Model
  • 4
    Best Graphdb
  • 4
    Highly-available
  • 2
    It's awesome, I wanted to try it
  • 2
    Great onboarding process
  • 2
    Great query language and built in data browser
  • 2
    Used by Crunchbase

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Cons of Blazegraph
Cons of Neo4j
    Be the first to leave a con
    • 9
      Comparably slow
    • 4
      Can't store a vertex as JSON
    • 1
      Doesn't have a managed cloud service at low cost

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    - No public GitHub repository available -

    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.

    What is Neo4j?

    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.

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    What companies use Blazegraph?
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    What tools integrate with Blazegraph?
    What tools integrate with Neo4j?

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    What are some alternatives to Blazegraph and Neo4j?
    JanusGraph
    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.
    OrientDB
    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
    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
    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.
    RedisGraph
    RedisGraph is a graph database developed from scratch on top of Redis, using the new Redis Modules API to extend Redis with new commands and capabilities. Its main features include: - Simple, fast indexing and querying - Data stored in RAM, using memory-efficient custom data structures - On disk persistence - Tabular result sets - Simple and popular graph query language (Cypher) - Data Filtering, Aggregation and ordering
    See all alternatives