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Graph Engine

4
29
+ 1
1
RedisGraph

31
107
+ 1
7
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Graph Engine vs RedisGraph: What are the differences?

Introduction:

Graph Engine and RedisGraph are both graph database management systems that provide efficient graph processing capabilities. However, there are key differences between the two that differentiate them in terms of performance, scalability, and features.

1. Query Language: Graph Engine uses the Language-Integrated Knowledge Query (LIKQ) language for querying, which integrates with C# and provides advanced functionalities for graph traversal. In contrast, RedisGraph uses a Cypher-like query language inspired by Neo4j, making it easier for developers familiar with Cypher to transition and query data.

2. Storage Model: Graph Engine uses a vertex-centric storage model, enabling efficient graph traversal by storing edges as attributes of vertices. On the other hand, RedisGraph adopts a property graph model, which stores nodes and relationships as first-class citizens, allowing for complex graph structures and properties to be represented in the database.

3. Replication and Sharding: RedisGraph supports replication and sharding out of the box, allowing for horizontal scaling and high availability in distributed environments. In comparison, Graph Engine does not have built-in support for replication and sharding, potentially limiting its scalability in large-scale deployments.

4. In-memory Processing: Graph Engine excels in in-memory graph processing, utilizing memory efficiently for real-time analytics and pattern matching. RedisGraph also leverages in-memory processing but provides disk persistence for durability, ensuring data integrity and fault tolerance in case of failures.

5. Community Support: RedisGraph is developed and maintained by Redis Labs, a well-established company in the database industry, ensuring ongoing support, updates, and documentation. Graph Engine, while supported by Microsoft Research, has a smaller community and may have limited resources for user assistance and development.

6. Ecosystem Integration: RedisGraph seamlessly integrates with the broader Redis ecosystem, allowing users to leverage other Redis modules and features, such as caching, pub/sub messaging, and transactions. Graph Engine, while compatible with Azure services and Microsoft products, may have less integration with third-party tools and technologies, limiting its interoperability in diverse software environments.

In Summary, Graph Engine and RedisGraph differ in query language, storage model, replication/sharding capabilities, in-memory processing, community support, and ecosystem integration, each catering to specific use cases and preferences in graph database management.

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Pros of Graph Engine
Pros of RedisGraph
  • 1
    Flexiable, very expressive, native C# works
  • 3
    10x – 600x faster than any other graph database
  • 2
    Cypher – graph query language
  • 1
    Great graphdb
  • 1
    Open source

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What is 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.

What is 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

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What companies use Graph Engine?
What companies use RedisGraph?
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What tools integrate with Graph Engine?
What tools integrate with RedisGraph?
    No integrations found
    What are some alternatives to Graph Engine and RedisGraph?
    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.
    MySQL
    The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
    PostgreSQL
    PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
    MongoDB
    MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
    Redis
    Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
    See all alternatives