Memgraph vs RedisGraph

Overview

RedisGraph

Stacks31

Followers107

Votes7

Memgraph

Stacks9

Followers19

Votes0

Memgraph vs RedisGraph: What are the differences?

Markdown code is used to format text in a way that can be easily converted to HTML. It provides a simple and efficient way to create and display content on websites.

Key difference 1: Cypher vs RediSearch query language: Memgraph uses the Cypher query language, which allows for expressive and flexible querying of graph data. RedisGraph, on the other hand, uses the RediSearch query language, which is a more simplified and efficient query language designed specifically for graph data.
Key difference 2: Replication and Scalability: Memgraph provides built-in replication and scalability features, allowing for the distribution of data across multiple servers and ensuring high availability. RedisGraph, on the other hand, does not provide native replication and scalability features and relies on external tools or libraries to achieve the same level of replication and scalability.
Key difference 3: Data Modeling: Memgraph supports property graph data model, allowing for the use of nodes, relationships, and properties to represent and query complex data structures. RedisGraph, on the other hand, follows the labeled property graph model, which only allows for the use of nodes and relationships without properties.
Key difference 4: Performance: Memgraph is specifically designed to handle large scale graph data efficiently, utilizing various optimization techniques such as indexing, caching, and parallel query execution. RedisGraph also provides good performance for graph data, but it may not be as efficient as Memgraph for extremely large datasets or complex graph operations.
Key difference 5: Community and Support: Memgraph has an active community and provides comprehensive documentation, tutorials, and support resources, making it easy for users to learn and get help when needed. RedisGraph also has a supportive community and documentation, but it may not have the same level of resources and support as Memgraph.
Key difference 6: Additional Features: Memgraph provides additional features such as built-in machine learning support, real-time analytics, and integration with popular programming languages. RedisGraph focuses primarily on graph data storage and querying, without providing extensive additional features or integrations.

In Summary, Memgraph and RedisGraph differ in terms of query language, replication and scalability, data modeling, performance, community and support, and additional features.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs

CLI (Node.js)

Manual

Detailed Comparison

RedisGraph	Memgraph
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	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.
-	Cypher Query Language; Bolt Protocol as Communication API; Push and Pull Communication Mechanisms; Authentication and Authorization; Data Import/Export; Data Visualization; Graph Database; Real-Time Data Analytics; Reporting & Statistics; Search/Filter; Audit Logs; High-availability Replication; Extensibility via Query and Auth Modules;
Statistics
Stacks 31	Stacks 9
Followers 107	Followers 19
Votes 7	Votes 0
Pros & Cons
Pros 3 10x – 600x faster than any other graph database 2 Cypher – graph query language 1 Open source 1 Great graphdb	No community feedback yet
Integrations
Redis	C++ Docker Google Cloud Platform Microsoft Azure Kubernetes Python GrapheneDB Red Hat OpenShift Graph Story

What are some alternatives to RedisGraph, Memgraph?

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.

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.

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.

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

Bootstrap vs Materialize

Django vs Laravel vs Node.js

Bootstrap vs Foundation vs Material UI

Node.js vs Spring-Boot

Flyway vs Liquibase

Memgraph vs RedisGraph: What are the differences?

Markdown code is used to format text in a way that can be easily converted to HTML. It provides a simple and efficient way to create and display content on websites.

Key difference 1: Cypher vs RediSearch query language: Memgraph uses the Cypher query language, which allows for expressive and flexible querying of graph data. RedisGraph, on the other hand, uses the RediSearch query language, which is a more simplified and efficient query language designed specifically for graph data.
Key difference 2: Replication and Scalability: Memgraph provides built-in replication and scalability features, allowing for the distribution of data across multiple servers and ensuring high availability. RedisGraph, on the other hand, does not provide native replication and scalability features and relies on external tools or libraries to achieve the same level of replication and scalability.
Key difference 3: Data Modeling: Memgraph supports property graph data model, allowing for the use of nodes, relationships, and properties to represent and query complex data structures. RedisGraph, on the other hand, follows the labeled property graph model, which only allows for the use of nodes and relationships without properties.
Key difference 4: Performance: Memgraph is specifically designed to handle large scale graph data efficiently, utilizing various optimization techniques such as indexing, caching, and parallel query execution. RedisGraph also provides good performance for graph data, but it may not be as efficient as Memgraph for extremely large datasets or complex graph operations.
Key difference 5: Community and Support: Memgraph has an active community and provides comprehensive documentation, tutorials, and support resources, making it easy for users to learn and get help when needed. RedisGraph also has a supportive community and documentation, but it may not have the same level of resources and support as Memgraph.
Key difference 6: Additional Features: Memgraph provides additional features such as built-in machine learning support, real-time analytics, and integration with popular programming languages. RedisGraph focuses primarily on graph data storage and querying, without providing extensive additional features or integrations.

In Summary, Memgraph and RedisGraph differ in terms of query language, replication and scalability, data modeling, performance, community and support, and additional features.