DBMS > etcd vs. IBM Db2 vs. Microsoft Azure Table Storage vs. PouchDB vs. SQLite

System Properties Comparison etcd vs. IBM Db2 vs. Microsoft Azure Table Storage vs. PouchDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Common in IBM host environments, 2 different versions for host and Windows/Linux

A Wide Column Store for rapid development using massive semi-structured datasets

JavaScript DBMS with an API inspired by CouchDB

Widely used embeddable, in-process RDBMS

Primary database model

Key-value store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Wide column store

Document store

Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

etcd.io
github.com/etcd-io/etcd

www.ibm.com/products/db2

azure.microsoft.com/en-us/services/storage/tables

pouchdb.com

www.sqlite.org

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.ibm.com/docs/en/db2

pouchdb.com/guides

www.sqlite.org/docs.html

Developer

IBM

Microsoft

Apache Software Foundation

Dwayne Richard Hipp

Initial release

1983

host version

2012

2000

Current release

3.4, August 2019

12.1, October 2016

7.1.1, June 2019

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free version is available

commercial

Open Source

Public Domain

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 and C++

JavaScript

Server operating systems

FreeBSD
Linux
Windows

experimental

AIX
HP-UX
Linux
Solaris
Windows
z/OS

hosted

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

server-less

Data scheme

schema-free

yes

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

SQL-92 is not fully supported

APIs and other access methods

gRPC
JSON over HTTP

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

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

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

yes

View functions in JavaScript

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

Sharding

Implicit feature of the cloud service

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes

with separate tools (MQ, InfoSphere)

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

fine grained access rights according to SQL-standard

Access rights based on private key authentication or shared access signatures

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