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Learn MorePros of Datahike
Pros of MongoDB
Pros of Datahike
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Pros of MongoDB
- Document-oriented storage828
- No sql593
- Ease of use553
- Fast464
- High performance410
- Free255
- Open source218
- Flexible180
- Replication & high availability145
- Easy to maintain112
- Querying42
- Easy scalability39
- Auto-sharding38
- High availability37
- Map/reduce31
- Document database27
- Easy setup25
- Full index support25
- Reliable16
- Fast in-place updates15
- Agile programming, flexible, fast14
- No database migrations12
- Easy integration with Node.Js8
- Enterprise8
- Enterprise Support6
- Great NoSQL DB5
- Support for many languages through different drivers4
- Schemaless3
- Aggregation Framework3
- Drivers support is good3
- Fast2
- Managed service2
- Easy to Scale2
- Awesome2
- Consistent2
- Good GUI1
- Acid Compliant1
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Cons of Datahike
Cons of MongoDB
Cons of Datahike
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Cons of MongoDB
- Very slowly for connected models that require joins6
- Not acid compliant3
- Proprietary query language2
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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?
What companies use Datahike?
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What companies use MongoDB?
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What tools integrate with Datahike?
What tools integrate with MongoDB?
What tools integrate with Datahike?
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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