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Akutan vs Graph Engine

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Akutan
6
32
+ 1
0
Graph Engine
4
29
+ 1
1
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Beam vs Graph Engine: 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 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.

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

Beam and Graph Engine are both open source tools. It seems that Graph Engine with 1.75K GitHub stars and 249 forks on GitHub has more adoption than Beam with 1.37K GitHub stars and 64 GitHub forks.

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Pros of Akutan
Pros of Graph Engine
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      Flexiable, very expressive, native C# works

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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 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.

    Need advice about which tool to choose?Ask the StackShare community!

    What companies use Akutan?
    What companies use Graph Engine?
      No companies found
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      What tools integrate with Akutan?
      What tools integrate with Graph Engine?
        No integrations found

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        What are some alternatives to Akutan and Graph Engine?
        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.
        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.
        See all alternatives

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