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  1. Stackups
  2. Application & Data
  3. Graph Databases
  4. Graph Databases
  5. Cayley vs DSE Graph

Cayley vs DSE Graph

OverviewComparisonAlternatives

Overview

Cayley
Cayley
Stacks25
Followers73
Votes7
DSE Graph
DSE Graph
Stacks4
Followers8
Votes0
GitHub Stars0
Forks0

Cayley vs DSE Graph: What are the differences?

Cayley: An open-source graph database. 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; DSE Graph: A distributed graph database that is optimized for enterprise applications. It is a distributed graph database that is optimized for enterprise applications–Zero downtime, fast traversals at scale, and analysis of complex, related datasets in real time.

Cayley and DSE Graph can be categorized as "Graph Databases" tools.

Some of the features offered by Cayley are:

  • Written in Go
  • Easy to get running (3 or 4 commands, below)
  • RESTful API

On the other hand, DSE Graph provides the following key features:

  • Graph Powered Insights
  • Graph Your Way
  • Graph Available Always

Cayley and DSE Graph are both open source tools. Cayley with 12.8K GitHub stars and 1.15K forks on GitHub appears to be more popular than DSE Graph with 7 GitHub stars and 2 GitHub forks.

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Detailed Comparison

Cayley
Cayley
DSE Graph
DSE Graph

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.

It is a distributed graph database that is optimized for enterprise applications–Zero downtime, fast traversals at scale, and analysis of complex, related datasets in real time.

Written in Go;Easy to get running (3 or 4 commands, below);RESTful API;or a REPL if you prefer;Built-in query editor and visualizer;Multiple query languages:;JavaScript, with a Gremlin-inspired* graph object.;(simplified) MQL, for Freebase fans;Plays well with multiple backend stores:;LevelDB;Bolt;MongoDB for distributed stores;In-memory, ephemeral;Modular design;easy to extend with new languages and backends;Good test coverage;Speed, where possible.
Graph Powered Insights; Graph Your Way; Graph Available Always
Statistics
GitHub Stars
-
GitHub Stars
0
GitHub Forks
-
GitHub Forks
0
Stacks
25
Stacks
4
Followers
73
Followers
8
Votes
7
Votes
0
Pros & Cons
Pros
  • 7
    Full open source
No community feedback yet
Integrations
No integrations available
Python
Python
.NET
.NET
JavaScript
JavaScript
Java
Java
Groovy
Groovy

What are some alternatives to Cayley, DSE Graph?

Neo4j

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.

Dgraph

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

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

Blazegraph

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

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

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

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

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

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

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.

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