Alternatives to CouchDB logo

Alternatives to CouchDB

MongoDB, Couchbase, Cloudant, MariaDB, and RethinkDB are the most popular alternatives and competitors to CouchDB.
395
417
+ 1
137

What is CouchDB and what are its top alternatives?

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.
CouchDB is a tool in the Databases category of a tech stack.
CouchDB is an open source tool with 4.7K GitHub stars and 937 GitHub forks. Here’s a link to CouchDB's open source repository on GitHub

Top Alternatives to CouchDB

  • MongoDB

    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

    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

    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

    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

    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. ...

  • Redis

    Redis

    Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets. ...

  • Riak

    Riak

    Riak is a distributed database designed to deliver maximum data availability by distributing data across multiple servers. As long as your client can reach one Riak server, it should be able to write data. In most failure scenarios, the data you want to read should be available, although it may not be the most up-to-date version of that data. ...

  • Cassandra

    Cassandra

    Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL. ...

CouchDB alternatives & related posts

related MongoDB posts

Jeyabalaji Subramanian

Recently we were looking at a few robust and cost-effective ways of replicating the data that resides in our production MongoDB to a PostgreSQL database for data warehousing and business intelligence.

We set ourselves the following criteria for the optimal tool that would do this job: - The data replication must be near real-time, yet it should NOT impact the production database - The data replication must be horizontally scalable (based on the load), asynchronous & crash-resilient

Based on the above criteria, we selected the following tools to perform the end to end data replication:

We chose MongoDB Stitch for picking up the changes in the source database. It is the serverless platform from MongoDB. One of the services offered by MongoDB Stitch is Stitch Triggers. Using stitch triggers, you can execute a serverless function (in Node.js) in real time in response to changes in the database. When there are a lot of database changes, Stitch automatically "feeds forward" these changes through an asynchronous queue.

We chose Amazon SQS as the pipe / message backbone for communicating the changes from MongoDB to our own replication service. Interestingly enough, MongoDB stitch offers integration with AWS services.

In the Node.js function, we wrote minimal functionality to communicate the database changes (insert / update / delete / replace) to Amazon SQS.

Next we wrote a minimal micro-service in Python to listen to the message events on SQS, pickup the data payload & mirror the DB changes on to the target Data warehouse. We implemented source data to target data translation by modelling target table structures through SQLAlchemy . We deployed this micro-service as AWS Lambda with Zappa. With Zappa, deploying your services as event-driven & horizontally scalable Lambda service is dumb-easy.

In the end, we got to implement a highly scalable near realtime Change Data Replication service that "works" and deployed to production in a matter of few days!

See more
Robert Zuber

We use MongoDB as our primary #datastore. Mongo's approach to replica sets enables some fantastic patterns for operations like maintenance, backups, and #ETL.

As we pull #microservices from our #monolith, we are taking the opportunity to build them with their own datastores using PostgreSQL. We also use Redis to cache data we’d never store permanently, and to rate-limit our requests to partners’ APIs (like GitHub).

When we’re dealing with large blobs of immutable data (logs, artifacts, and test results), we store them in Amazon S3. We handle any side-effects of S3’s eventual consistency model within our own code. This ensures that we deal with user requests correctly while writes are in process.

See more

related Couchbase posts

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.

See more
Gabriel Pa

If you want to use Pouchdb might as well use RxDB which is an observables wrapper for Pouch but much more comfortable to use. Realm is awesome but Pouchdb and RxDB give you more control. You can use Couchbase (recommended) or CouchDB to enable 2-way sync

See more
Cloudant logo

Cloudant

43
55
22
Distributed database-as-a-service (DBaaS) for web & mobile apps.
43
55
+ 1
22
CONS OF CLOUDANT
    No cons available

    related Cloudant posts

    Josh Dzielak
    Co-Founder & CTO at Orbit · | 5 upvotes · 145.3K views

    As a side project, I was building a note taking app that needed to synchronize between the client and the server so that it would work offline. At first I used Firebase to store the data on the server and wrote my own code to cache Firebase data in local storage and synchronize it. This was brittle and not performant. I figured that someone else must have solved this in a better way so I went looking for a better solution.

    I needed a tool where I could write the data once and it would write to client and server, and when clients came back on line they would automatically catch the client up. I also needed conflict resolution. I was thrilled to discover Pouchdb and its server-side counterpart CouchDB. Together, they met nearly all of my requirements and were very easy to implement - I was able to remove a ton of custom code and have found the synchronization to be very robust. Pouchdb 7 has improved mobile support too, so I can run the app on iOS or Android browsers.

    My Couchdb instance is actually a Cloudant instance running on IBM Bluemix. For my fairly low level of API usage, it's been totally free, and it has a decent GUI for managing users and replications.

    See more
    MariaDB logo

    MariaDB

    8.3K
    5.8K
    471
    An enhanced, drop-in replacement for MySQL
    8.3K
    5.8K
    + 1
    471

    related MariaDB posts

    I'm researching what Technology Stack I should use to build my product (something like food delivery App) for Web, iOS, and Android Apps. Please advise which technologies you would recommend from a Scalability, Reliability, Cost, and Efficiency standpoint for a start-up. Here are the technologies I came up with, feel free to suggest any new technology even it's not in the list below.

    For Mobile Apps -

    1. native languages like Swift for IOS and Java/Kotlin for Android
    2. or cross-platform languages like React Native for both IOS and Android Apps

    For UI -

    1. React

    For Back-End or APIs -

    1. Node.js
    2. PHP

    For Database -

    1. PostgreSQL
    2. MySQL
    3. Cloud Firestore
    4. MariaDB

    Thanks!

    See more

    We initially started out with Heroku as our PaaS provider due to a desire to use it by our original developer for our Ruby on Rails application/website at the time. We were finding response times slow, it was painfully slow, sometimes taking 10 seconds to start loading the main page. Moving up to the next "compute" level was going to be very expensive.

    We moved our site over to AWS Elastic Beanstalk , not only did response times on the site practically become instant, our cloud bill for the application was cut in half.

    In database world we are currently using Amazon RDS for PostgreSQL also, we have both MariaDB and Microsoft SQL Server both hosted on Amazon RDS. The plan is to migrate to AWS Aurora Serverless for all 3 of those database systems.

    Additional services we use for our public applications: AWS Lambda, Python, Redis, Memcached, AWS Elastic Load Balancing (ELB), Amazon Elasticsearch Service, Amazon ElastiCache

    See more

    related RethinkDB posts

    Łukasz Korecki
    CTO & Co-founder at EnjoyHQ · | 12 upvotes · 118.3K views

    We initially chose RethinkDB because of the schema-less document store features, and better durability resilience/story than MongoDB In the end, it didn't work out quite as we expected: there's plenty of scalability issues, it's near impossible to run analytical workloads and small community makes working with Rethink a challenge. We're in process of migrating all our workloads to PostgreSQL and hopefully, we will be able to decommission our RethinkDB deployment soon.

    See more

    related Redis posts

    Robert Zuber

    We use MongoDB as our primary #datastore. Mongo's approach to replica sets enables some fantastic patterns for operations like maintenance, backups, and #ETL.

    As we pull #microservices from our #monolith, we are taking the opportunity to build them with their own datastores using PostgreSQL. We also use Redis to cache data we’d never store permanently, and to rate-limit our requests to partners’ APIs (like GitHub).

    When we’re dealing with large blobs of immutable data (logs, artifacts, and test results), we store them in Amazon S3. We handle any side-effects of S3’s eventual consistency model within our own code. This ensures that we deal with user requests correctly while writes are in process.

    See more

    I'm working as one of the engineering leads in RunaHR. As our platform is a Saas, we thought It'd be good to have an API (We chose Ruby and Rails for this) and a SPA (built with React and Redux ) connected. We started the SPA with Create React App since It's pretty easy to start.

    We use Jest as the testing framework and react-testing-library to test React components. In Rails we make tests using RSpec.

    Our main database is PostgreSQL, but we also use MongoDB to store some type of data. We started to use Redis  for cache and other time sensitive operations.

    We have a couple of extra projects: One is an Employee app built with React Native and the other is an internal back office dashboard built with Next.js for the client and Python in the backend side.

    Since we have different frontend apps we have found useful to have Bit to document visual components and utils in JavaScript.

    See more
    Riak logo

    Riak

    89
    106
    36
    A distributed, decentralized data storage system
    89
    106
    + 1
    36

    related Riak posts

    Cassandra logo

    Cassandra

    3K
    2.8K
    462
    A partitioned row store. Rows are organized into tables with a required primary key.
    3K
    2.8K
    + 1
    462

    related Cassandra posts

    Thierry Schellenbach
    Shared insights
    on
    Redis
    Cassandra
    RocksDB
    at

    1.0 of Stream leveraged Cassandra for storing the feed. Cassandra is a common choice for building feeds. Instagram, for instance started, out with Redis but eventually switched to Cassandra to handle their rapid usage growth. Cassandra can handle write heavy workloads very efficiently.

    Cassandra is a great tool that allows you to scale write capacity simply by adding more nodes, though it is also very complex. This complexity made it hard to diagnose performance fluctuations. Even though we had years of experience with running Cassandra, it still felt like a bit of a black box. When building Stream 2.0 we decided to go for a different approach and build Keevo. Keevo is our in-house key-value store built upon RocksDB, gRPC and Raft.

    RocksDB is a highly performant embeddable database library developed and maintained by Facebook’s data engineering team. RocksDB started as a fork of Google’s LevelDB that introduced several performance improvements for SSD. Nowadays RocksDB is a project on its own and is under active development. It is written in C++ and it’s fast. Have a look at how this benchmark handles 7 million QPS. In terms of technology it’s much more simple than Cassandra.

    This translates into reduced maintenance overhead, improved performance and, most importantly, more consistent performance. It’s interesting to note that LinkedIn also uses RocksDB for their feed.

    #InMemoryDatabases #DataStores #Databases

    See more

    React AngularJS jQuery

    Laravel Zend Framework

    MySQL MongoDB Cassandra

    Docker

    Linux

    See more