DBMS > CouchDB vs. Google Cloud Spanner vs. SpatiaLite vs. SQL.JS vs. SQLite

System Properties Comparison CouchDB vs. Google Cloud Spanner vs. SpatiaLite vs. SQL.JS vs. SQLite

Editorial information provided by DB-Engines

Name

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Spatial extension of SQLite

Port of SQLite to JavaScript

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

Relational DBMS

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

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

couchdb.apache.org

cloud.google.com/spanner

www.gaia-gis.it/fossil/libspatialite/index

sql.js.org

www.sqlite.org

Technical documentation

docs.couchdb.org/en/stable

cloud.google.com/spanner/docs

www.gaia-gis.it/gaia-sins/spatialite_topics.html

sql.js.org/documentation/index.html

www.sqlite.org/docs.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Google

Alessandro Furieri

Alon Zakai

enhancements implemented by others

Dwayne Richard Hipp

Initial release

2005

2017

2008

2012

2000

Current release

3.3.3, December 2023

5.0.0, August 2020

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

C++

JavaScript

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

hosted

server-less

server-less, requires a JavaScript environment (browser, Node.js)

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

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

via views

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

SQL-92 is not fully supported

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP/JSON API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Go
Java
JavaScript (Node.js)
Python

JavaScript

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

Server-side scripts

Stored procedures

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication with 3 replicas for regional instances.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

via file-system locks

Durability

Support for making data persistent

yes

except by serializing a db to a file

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users can be defined per database

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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