Neo4j vs RecallGraph
Overview
🔥 Trending in Graph Databases on StackShare
Detailed Comparison
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 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. |
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 | Create single/multiple documents (vertices/edges);
Replace entire single/multiple documents with new content;
Delete single/multiple documents;
Add/Update specific fields in single/multiple documents;
Restore deleted nodes back to their last known undeleted state;
Point-in-time checkouts;
Async implicit commits |
Statistics | |
GitHub Stars 15.3K | GitHub Stars 342 |
GitHub Forks 2.5K | GitHub Forks 25 |
Stacks 1.2K | Stacks 1 |
Followers 1.4K | Followers 4 |
Votes 351 | Votes 0 |
Pros & Cons | |
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What are some alternatives to Neo4j, RecallGraph?
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.
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.
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.
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.
