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

DSE Graph vs Grakn

OverviewComparisonAlternatives

Overview

DSE Graph
DSE Graph
Stacks4
Followers8
Votes0
GitHub Stars0
Forks0
TypeDB
TypeDB
Stacks11
Followers34
Votes0

DSE Graph vs Grakn: What are the differences?

Developers describe DSE Graph as "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. On the other hand, Grakn is detailed as "An intelligent database - a knowledge graph". It is an intelligent database: a knowledge graph engine to organise complex networks of data and making it queryable, by performing knowledge engineering. Rooted in Knowledge Representation and Automated Reasoning, it provides the knowledge foundation for cognitive and intelligent (e.g. AI) systems, by providing an intelligent language for modelling, transactions and analytics. Being a distributed database, it is designed to scale over a network of computers through partitioning and replication.

DSE Graph and Grakn can be primarily classified as "Graph Databases" tools.

Some of the features offered by DSE Graph are:

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

On the other hand, Grakn provides the following key features:

  • Distributed Analytics
  • Automated Reasoning
  • Higher-Level Language

Grakn is an open source tool with 2K GitHub stars and 234 GitHub forks. Here's a link to Grakn's open source repository on GitHub.

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Detailed Comparison

DSE Graph
DSE Graph
TypeDB
TypeDB

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.

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

Graph Powered Insights; Graph Your Way; Graph Available Always
Distributed Analytics; Automated Reasoning; Higher-Level Language
Statistics
GitHub Stars
0
GitHub Stars
-
GitHub Forks
0
GitHub Forks
-
Stacks
4
Stacks
11
Followers
8
Followers
34
Votes
0
Votes
0
Integrations
Python
Python
.NET
.NET
JavaScript
JavaScript
Java
Java
Groovy
Groovy
No integrations available

What are some alternatives to DSE Graph, TypeDB?

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

Cayley

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

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.

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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