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CouchDB vs Redis: What are the differences?

Introduction

In this article, we will discuss the key differences between CouchDB and Redis.

  1. Data Model: CouchDB is a document-oriented database, where data is organized and accessed in the form of JSON documents. It allows for flexible and dynamic schemas, making it suitable for semi-structured and unstructured data. On the other hand, Redis is a key-value store that stores data in a simple key-value format without any complex structures or relationships.

  2. Scalability and Performance: CouchDB is designed to scale horizontally, allowing for distributed deployments across multiple nodes. It offers automatic sharding and replication capabilities, ensuring high availability and fault tolerance. Redis, on the other hand, is single-threaded and primarily runs in memory, which makes it extremely fast for read and write operations. It offers master-slave replication but lacks built-in sharding capabilities.

  3. Querying and Indexing: CouchDB uses MapReduce for querying and indexing data. It supports views, which are predefined queries that can be used to retrieve data based on specific conditions. These views are written in JavaScript using map and reduce functions. In contrast, Redis provides a variety of data structures like sets, lists, and sorted sets, with the ability to perform atomic operations on these structures. It also supports various query commands for retrieving and manipulating data.

  4. Data Persistence: CouchDB provides durable storage by writing data to disk, ensuring data is not lost on system crashes or failures. It supports a write-ahead log and an append-only file for durability. Redis, on the other hand, allows data persistence through snapshots and append-only files. It also provides optional replication for data redundancy.

  5. Data Consistency and Concurrency: CouchDB offers a concept called eventual consistency, where changes to the database are eventually propagated to all replicas or nodes. It ensures that all replicas eventually reach the same state but may experience temporary inconsistency. Redis, on the other hand, provides strong data consistency by using a single-threaded model. It also supports transactions and optimistic locking for handling concurrency.

  6. Use Cases: CouchDB is suitable for applications that require flexible schemas, offline availability, and continuous replication, such as mobile applications and collaborative platforms. Redis, on the other hand, excels in use cases that require fast data access, caching, real-time analytics, and message queues, such as session management, leaderboard systems, and job queues.

In Summary, CouchDB and Redis differ in their data models, scalability, querying capabilities, data persistence, consistency, and use cases.

Decisions about CouchDB and Redis
Gabriel Pa

We implemented our first large scale EPR application from naologic.com using CouchDB .

Very fast, replication works great, doesn't consume much RAM, queries are blazing fast but we found a problem: the queries were very hard to write, it took a long time to figure out the API, we had to go and write our own @nodejs library to make it work properly.

It lost most of its support. Since then, we migrated to Couchbase and the learning curve was steep but all worth it. Memcached indexing out of the box, full text search works great.

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Pros of CouchDB
Pros of Redis
  • 43
    JSON
  • 30
    Open source
  • 18
    Highly available
  • 12
    Partition tolerant
  • 11
    Eventual consistency
  • 7
    Sync
  • 5
    REST API
  • 4
    Attachments mechanism to docs
  • 4
    Multi master replication
  • 3
    Changes feed
  • 1
    REST interface
  • 1
    js- and erlang-views
  • 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 CouchDB
Cons of Redis
    Be the first to leave a con
    • 15
      Cannot query objects directly
    • 3
      No secondary indexes for non-numeric data types
    • 1
      No WAL

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    - No public GitHub repository available -

    What is CouchDB?

    Apache CouchDB is a database that uses JSON for documents, JavaScript for MapReduce indexes, and regular HTTP for its API. CouchDB is a database that completely embraces the web. Store your data with JSON documents. Access your documents and query your indexes with your web browser, via HTTP. Index, combine, and transform your documents with JavaScript.

    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 are some alternatives to CouchDB 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.
    Couchbase
    Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.
    Cloudant
    Cloudant’s distributed database as a service (DBaaS) allows developers of fast-growing web and mobile apps to focus on building and improving their products, instead of worrying about scaling and managing databases on their own.
    MariaDB
    Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.
    RethinkDB
    RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.
    See all alternatives