DBMS > Couchbase vs. RethinkDB vs. SQLite vs. SwayDB

System Properties Comparison Couchbase vs. RethinkDB vs. SQLite vs. SwayDB

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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

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Widely used embeddable, in-process RDBMS

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Document store

Relational DBMS

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	2.74
Rank	#105	Overall
	#19	Document stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

Technical documentation

docs.couchbase.com

rethinkdb.com/docs

www.sqlite.org/docs.html

Developer

Couchbase, Inc.

The Linux Foundation

since July 2017

Dwayne Richard Hipp

Simer Plaha

Initial release

2011

2009

2000

2018

Current release

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

2.4.1, August 2020

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

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

Open Source

Apache Version 2

Open Source

Public Domain

Open Source

GNU Affero GPL V3.0

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

C++

Scala

Server operating systems

Linux
OS X
Windows

server-less

Data scheme

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL-92 is not fully supported

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Java
Kotlin
Scala

Server-side scripts

Stored procedures

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

Triggers

yes

via the TAP protocol

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-document operations

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

via file-system locks

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.

yes

users and table-level permissions

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