DBMS > Couchbase vs. mSQL vs. OrientDB vs. RocksDB

System Properties Comparison Couchbase vs. mSQL vs. OrientDB vs. RocksDB

Please select another system to include it in the comparison.

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

Multi-model DBMS (Document, Graph, Key/Value)

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

Primary database model

Document store

Relational DBMS

Document store
Graph DBMS
Key-value 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

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

www.couchbase.com

hughestech.com.au/products/msql

orientdb.org

rocksdb.org

Technical documentation

docs.couchbase.com

www.orientdb.com/docs/last/index.html

github.com/facebook/rocksdb/wiki

Developer

Couchbase, Inc.

Hughes Technologies

OrientDB LTD; CallidusCloud; SAP

Facebook, Inc.

Initial release

2011

1994

2010

2013

Current release

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

4.4, October 2021

3.2.29, March 2024

9.2.1, May 2024

License

Commercial or Open Source

Open Source

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

commercial

free licenses can be provided

Open Source

Apache version 2

Open Source

BSD

Cloud-based only

Only available as a cloud service

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

Java

C++

Server operating systems

Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

All OS with a Java JDK (>= JDK 6)

Linux

Data scheme

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

Typing

predefined data types such as float or date

yes

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

SQL

Support of SQL

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

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like query language, no joins

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

JDBC
ODBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

C++ API
Java API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

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

Java, Javascript

Triggers

yes

via the TAP protocol

Hooks

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

none

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

none

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

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

User concepts

Access control

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

Access rights for users and roles; record level security configurable

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.