Blazegraph vs Neo4j

Overview

Neo4j

Stacks1.2K

Followers1.4K

Votes351

GitHub Stars15.3K

Forks2.5K

Blazegraph

Stacks7

Followers16

Votes3

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.

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.
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.
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.
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.
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.
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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CLI (Node.js)

Manual

Detailed Comparison

Neo4j	Blazegraph
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 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.
intuitive, using a graph model for data representation;reliable, with full ACID transactions;durable and fast, using a custom disk-based, native storage engine;massively scalable, up to several billion nodes/relationships/properties;highly-available, when distributed across multiple machines;expressive, with a powerful, human readable graph query language;fast, with a powerful traversal framework for high-speed graph queries;embeddable, with a few small jars;simple, accessible by a convenient REST interface or an object-oriented Java API	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
Statistics
GitHub Stars 15.3K	GitHub Stars -
GitHub Forks 2.5K	GitHub Forks -
Stacks 1.2K	Stacks 7
Followers 1.4K	Followers 16
Votes 351	Votes 3
Pros & Cons
Pros 69 Cypher – graph query language 61 Great graphdb 33 Open source 31 Rest api 27 High-Performance Native API Cons 9 Comparably slow 4 Can't store a vertex as JSON 1 Doesn't have a managed cloud service at low cost	Pros 1 Support for RDF 1 Easy Setup and Use 1 Support for SPARQL
Integrations
No integrations available	Structr Graph Story Cartography GrapheneDB Linkurious

What are some alternatives to Neo4j, Blazegraph?

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.

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

Cayley

Cayley is an open-source graph inspired by the graph database behind Freebase and Google's Knowledge Graph. Its goal is to be a part of the developer's toolbox where Linked Data and graph-shaped data (semantic webs, social networks, etc) in general are concerned.

Graph Engine

The distributed RAM store provides a globally addressable high-performance key-value store over a cluster of machines. Through the RAM store, GE enables the fast random data access power over a large distributed data set.

FalkorDB

FalkorDB is developing a novel graph database that revolutionizes the graph databases and AI industries. Our graph database is based on novel but proven linear algebra algorithms on sparse matrices that deliver unprecedented performance up to two orders of magnitude greater than the leading graph databases. Our goal is to provide the missing piece in AI in general and LLM in particular, reducing hallucinations and enhancing accuracy and reliability. We accomplish this by providing a fast and interactive knowledge graph, which provides a superior solution to the common solutions today.

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.

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.

TypeDB

TypeDB is a database with a rich and logical type system. TypeDB empowers you to solve complex problems, using TypeQL as its query language.

Memgraph

Memgraph is a streaming graph application platform that helps you wrangle your streaming data, build sophisticated models that you can query in real-time, and develop applications you never thought possible in days, not months.

Nebula Graph

It is an open source distributed graph database. It has a shared-nothing architecture and scales quite well due to the separation of storage and computation. It can handle hundreds of billions of vertices and trillions of edges while still maintaining milliseconds of latency. It is openCypher compatible.

Related Comparisons

Blazegraph vs Neo4j: What are the differences?

Introduction

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.
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.
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.
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.
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.
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.

Blazegraph vs Neo4j

Overview