Grakn vs Graph Engine

Overview

Graph Engine

Stacks4

Followers29

Votes1

GitHub Stars2.2K

Forks331

TypeDB

Stacks11

Followers34

Votes0

Graph Engine vs Grakn: What are the differences?

What is Graph Engine? RAM Store + Computation Engine + Graph Model (by Microsoft). 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.

What is Grakn? 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.

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

Graph Engine and Grakn are both open source tools. Grakn with 2K GitHub stars and 234 forks on GitHub appears to be more popular than Graph Engine with 1.85K GitHub stars and 270 GitHub forks.

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Detailed Comparison

Graph Engine	TypeDB
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.	TypeDB is a database with a rich and logical type system. TypeDB empowers you to solve complex problems, using TypeQL as its query language.
-	Distributed Analytics; Automated Reasoning; Higher-Level Language
Statistics
GitHub Stars 2.2K	GitHub Stars -
GitHub Forks 331	GitHub Forks -
Stacks 4	Stacks 11
Followers 29	Followers 34
Votes 1	Votes 0
Pros & Cons
Pros 1 Flexiable, very expressive, native C# works	No community feedback yet

What are some alternatives to Graph Engine, TypeDB?

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'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.

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.

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.