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Datahike

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MongoDB

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Pros of Datahike
Pros of MongoDB
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    • 828
      Document-oriented storage
    • 593
      No sql
    • 553
      Ease of use
    • 464
      Fast
    • 410
      High performance
    • 255
      Free
    • 218
      Open source
    • 180
      Flexible
    • 145
      Replication & high availability
    • 112
      Easy to maintain
    • 42
      Querying
    • 39
      Easy scalability
    • 38
      Auto-sharding
    • 37
      High availability
    • 31
      Map/reduce
    • 27
      Document database
    • 25
      Easy setup
    • 25
      Full index support
    • 16
      Reliable
    • 15
      Fast in-place updates
    • 14
      Agile programming, flexible, fast
    • 12
      No database migrations
    • 8
      Easy integration with Node.Js
    • 8
      Enterprise
    • 6
      Enterprise Support
    • 5
      Great NoSQL DB
    • 4
      Support for many languages through different drivers
    • 3
      Schemaless
    • 3
      Aggregation Framework
    • 3
      Drivers support is good
    • 2
      Fast
    • 2
      Managed service
    • 2
      Easy to Scale
    • 2
      Awesome
    • 2
      Consistent
    • 1
      Good GUI
    • 1
      Acid Compliant

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    Cons of Datahike
    Cons of MongoDB
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      • 6
        Very slowly for connected models that require joins
      • 3
        Not acid compliant
      • 2
        Proprietary query language

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      What is Datahike?

      It is a durable Datalog database powered by an efficient Datalog query engine. It is considered usable for medium-sized projects.

      What is 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.

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      What companies use Datahike?
      What companies use MongoDB?
        No companies found
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        What tools integrate with Datahike?
        What tools integrate with MongoDB?

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        What are some alternatives to Datahike and MongoDB?
        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.
        Amazon S3
        Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web
        See all alternatives