DBMS > Couchbase vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. RocksDB vs. Tkrzw

System Properties Comparison Couchbase vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. RocksDB vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Database as a Service offering based on Apache CouchDB

Globally distributed, horizontally scalable, multi-model database service

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.couchbase.com

www.ibm.com/products/cloudant

azure.microsoft.com/services/cosmos-db

rocksdb.org

dbmx.net/tkrzw

Technical documentation

docs.couchbase.com

cloud.ibm.com/docs/Cloudant

learn.microsoft.com/azure/cosmos-db

github.com/facebook/rocksdb/wiki

Developer

Couchbase, Inc.

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

Facebook, Inc.

Mikio Hirabayashi

Initial release

2011

2010

2014

2013

2020

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

8.11.4, April 2024

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

Open Source

BSD

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Go and Erlang

Erlang

C++

Server operating systems

Linux
OS X
Windows

hosted

Linux

Linux
macOS

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

JSON types

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-like query language

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

RESTful HTTP/JSON API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

C++ API
Java API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C
C++
Go
Java
Perl
Python
Ruby

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

View functions (Map-Reduce) in JavaScript

JavaScript

Triggers

yes

via the TAP protocol

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

Implicit feature of the cloud service

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

atomic operations within a document possible

Multi-item ACID transactions with snapshot isolation within a partition

yes

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Ephemeral buckets

yes

using specific database classes

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Access rights for users can be defined per database

Access rights can be defined down to the item level

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