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  1. Stackups
  2. Application & Data
  3. Graph Databases
  4. Graph Databases
  5. Memgraph vs Neo4j

Memgraph vs Neo4j

OverviewComparisonAlternatives

Overview

Neo4j
Neo4j
Stacks1.2K
Followers1.4K
Votes351
GitHub Stars15.3K
Forks2.5K
Memgraph
Memgraph
Stacks9
Followers19
Votes0

Memgraph vs Neo4j: What are the differences?

Introduction Memgraph and Neo4j are both popular graph database management systems that offer powerful features for storing and querying graph data. However, there are key differences between these two options that users should consider when choosing the right graph database for their specific needs.

  1. Performance: Memgraph is designed to deliver superior performance in terms of both read and write operations. It utilizes various optimizations like multi-threading and lock-free data structures to achieve high throughput. On the other hand, Neo4j may not offer the same level of performance as Memgraph, especially for large-scale graph databases with complex queries.

  2. Scalability: Memgraph provides native sharding support, allowing users to distribute the data across multiple machines seamlessly. This enables horizontal scalability and ensures high availability and fault tolerance. In contrast, Neo4j offers limited scalability options, as it relies heavily on a single master node architecture, which can become a bottleneck for performance and scalability when dealing with large graph databases.

  3. Ease of Use: Memgraph has a simple and intuitive query language called Cypher, which is easy to learn and use. It offers a wide array of built-in functions and operators to perform complex graph queries efficiently. Neo4j, on the other hand, uses its own query language called CQL (Cypher Query Language), which has a similar syntax to Cypher but may require more time to learn for users who are already familiar with Cypher.

  4. Community and Support: Neo4j has been around for a longer time and has a larger community of users and contributors. It has a well-established ecosystem with numerous resources, forums, and libraries available. Memgraph, being a relatively newer graph database, may have a smaller community and limited resources in comparison.

  5. Pricing and Licensing: Memgraph offers a free Community Edition that is open-source and can be used for commercial purposes. It also provides a paid Enterprise Edition with additional features and support. Neo4j follows a similar model, with a free Community Edition and various paid editions with advanced features and support. The pricing and licensing models may vary between the two solutions, so users should evaluate their specific needs and budget when making a decision.

  6. Ecosystem Integration: Neo4j has a strong integration with other popular technologies and frameworks like Java, Python, and various graph visualization libraries. It provides official drivers and plugins to connect and interact with these tools seamlessly. Memgraph, being a newer entrant, may have a smaller integration ecosystem currently but is actively working on enhancing its compatibility with existing tools and frameworks.

In summary, Memgraph offers enhanced performance, scalability, simplicity, pricing model, and ecosystem integration, while Neo4j has a larger community and support. Choosing between the two graph databases depends on specific requirements, preferences, and the trade-offs users are willing to make.

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Detailed Comparison

Neo4j
Neo4j
Memgraph
Memgraph

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.

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.

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
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
GitHub Stars
15.3K
GitHub Stars
-
GitHub Forks
2.5K
GitHub Forks
-
Stacks
1.2K
Stacks
9
Followers
1.4K
Followers
19
Votes
351
Votes
0
Pros & Cons
Pros
  • 69
    Cypher – graph query language
  • 61
    Great graphdb
  • 33
    Open source
  • 31
    Rest api
  • 27
    High-Performance Native API
Cons
  • 9
    Comparably slow
  • 4
    Can't store a vertex as JSON
  • 1
    Doesn't have a managed cloud service at low cost
No community feedback yet
Integrations
No integrations available
C++
C++
Docker
Docker
Google Cloud Platform
Google Cloud Platform
Microsoft Azure
Microsoft Azure
Kubernetes
Kubernetes
Python
Python
GrapheneDB
GrapheneDB
Red Hat OpenShift
Red Hat OpenShift
Graph Story
Graph Story

What are some alternatives to Neo4j, Memgraph?

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.

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.

Nebula Graph

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.

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