Akutan

4
26
+ 1
0
RedisGraph

14
41
+ 1
0
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Beam vs RedisGraph: What are the differences?

What is Beam? A Distributed Knowledge Graph Store. A distributed knowledge graph store. Knowledge graphs are suitable for modeling data that is highly interconnected by many types of relationships, like encyclopedic information about the world.

What is RedisGraph? A High Performance In-Memory Graph Database as a Redis Module. 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.

Beam and RedisGraph can be categorized as "Graph Databases" tools.

Beam and RedisGraph are both open source tools. It seems that Beam with 1.37K GitHub stars and 64 forks on GitHub has more adoption than RedisGraph with 708 GitHub stars and 67 GitHub forks.

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What is Akutan?

A distributed knowledge graph store. Knowledge graphs are suitable for modeling data that is highly interconnected by many types of relationships, like encyclopedic information about the world.

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
What companies use Akutan?
What companies use RedisGraph?
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    What tools integrate with Akutan?
    What tools integrate with RedisGraph?

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    What are some alternatives to Akutan and RedisGraph?
    Apache Beam
    It implements batch and streaming data processing jobs that run on any execution engine. It executes pipelines on multiple execution environments.
    Apache Spark
    Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
    Apache Flink
    Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
    Arc
    Arc is designed for exploratory programming: the kind where you decide what to write by writing it. A good medium for exploratory programming is one that makes programs brief and malleable, so that's what we've aimed for. This is a medium for sketching software.
    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.
    See all alternatives
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