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MapDB vs Redis: What are the differences?

Key Differences between MapDB and Redis

MapDB and Redis are both popular databases used for storing and managing data, but they have some key differences that set them apart. Here are the main differences between MapDB and Redis:

  1. Data Storage: MapDB is an embedded database that stores data on the disk in a binary format. It can be used as an in-memory database or as a persistent storage solution. Redis, on the other hand, is an in-memory data structure store and can be used as a cache or a database. It stores data in RAM, but it also provides an option to persist data to disk.

  2. Data Structures: MapDB provides a wide range of data structures such as maps, sets, queues, and lists. It supports concurrent access and can be used in multi-threaded environments. Redis, on the other hand, provides a smaller set of data structures such as strings, lists, sets, and sorted sets. It excels at performing operations on these data structures in a highly efficient manner.

  3. Query Language: MapDB does not have a dedicated query language and relies on traditional Java APIs for data access and manipulation. It allows custom query operations to be performed using the Java programming language. Redis, on the other hand, provides its own query language called RedisQL. It allows users to perform complex operations on data using a simple and intuitive syntax.

  4. Scalability: MapDB is designed to work on a single machine and does not provide built-in support for distributed computing. It can scale vertically by adding more powerful hardware with larger storage capacity. Redis, on the other hand, is designed to be highly scalable and can be deployed in a distributed environment. It uses a master-slave replication model and supports sharding to achieve high availability and performance.

  5. Durability: MapDB provides durability by persisting data to disk in a transactional manner. It also supports various data backup strategies to prevent data loss. Redis, on the other hand, provides durability by periodically writing data to disk. It also supports replication and clustering to ensure high availability and data persistence.

  6. Community and Ecosystem: MapDB has a smaller community and ecosystem compared to Redis. Redis has a large and active community of users and contributors. It has a wide range of libraries, tools, and integrations available, making it easier to integrate with other platforms and systems.

In summary, MapDB is a versatile embedded database with a focus on data storage and retrieval, while Redis is an in-memory data structure store designed for high performance and scalability.

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Pros of MapDB
Pros of Redis
    Be the first to leave a pro
    • 886
      Performance
    • 542
      Super fast
    • 513
      Ease of use
    • 444
      In-memory cache
    • 324
      Advanced key-value cache
    • 194
      Open source
    • 182
      Easy to deploy
    • 164
      Stable
    • 155
      Free
    • 121
      Fast
    • 42
      High-Performance
    • 40
      High Availability
    • 35
      Data Structures
    • 32
      Very Scalable
    • 24
      Replication
    • 22
      Great community
    • 22
      Pub/Sub
    • 19
      "NoSQL" key-value data store
    • 16
      Hashes
    • 13
      Sets
    • 11
      Sorted Sets
    • 10
      NoSQL
    • 10
      Lists
    • 9
      Async replication
    • 9
      BSD licensed
    • 8
      Bitmaps
    • 8
      Integrates super easy with Sidekiq for Rails background
    • 7
      Keys with a limited time-to-live
    • 7
      Open Source
    • 6
      Lua scripting
    • 6
      Strings
    • 5
      Awesomeness for Free
    • 5
      Hyperloglogs
    • 4
      Transactions
    • 4
      Outstanding performance
    • 4
      Runs server side LUA
    • 4
      LRU eviction of keys
    • 4
      Feature Rich
    • 4
      Written in ANSI C
    • 4
      Networked
    • 3
      Data structure server
    • 3
      Performance & ease of use
    • 2
      Dont save data if no subscribers are found
    • 2
      Automatic failover
    • 2
      Easy to use
    • 2
      Temporarily kept on disk
    • 2
      Scalable
    • 2
      Existing Laravel Integration
    • 2
      Channels concept
    • 2
      Object [key/value] size each 500 MB
    • 2
      Simple

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    Cons of MapDB
    Cons of Redis
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      • 15
        Cannot query objects directly
      • 3
        No secondary indexes for non-numeric data types
      • 1
        No WAL

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      What is MapDB?

      MapDB provides Java Maps, Sets, Lists, Queues and other collections backed by off-heap or on-disk storage. It is a hybrid between java collection framework and embedded database engine. It is free and open-source under Apache license.

      What is 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.

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        What tools integrate with MapDB?
        What tools integrate with Redis?

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        What are some alternatives to MapDB and Redis?
        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.
        RocksDB
        RocksDB is an embeddable persistent key-value store for fast storage. RocksDB can also be the foundation for a client-server database but our current focus is on embedded workloads. RocksDB builds on LevelDB to be scalable to run on servers with many CPU cores, to efficiently use fast storage, to support IO-bound, in-memory and write-once workloads, and to be flexible to allow for innovation.
        LevelDB
        It is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values. It has been ported to a variety of Unix-based systems, macOS, Windows, and Android.
        Lucene
        Lucene Core, our flagship sub-project, provides Java-based indexing and search technology, as well as spellchecking, hit highlighting and advanced analysis/tokenization capabilities.
        Ehcache
        Ehcache is an open source, standards-based cache for boosting performance, offloading your database, and simplifying scalability. It's the most widely-used Java-based cache because it's robust, proven, and full-featured. Ehcache scales from in-process, with one or more nodes, all the way to mixed in-process/out-of-process configurations with terabyte-sized caches.
        See all alternatives