DBMS > CouchDB vs. HBase vs. IBM Db2 warehouse vs. SAP SQL Anywhere vs. VoltDB

System Properties Comparison CouchDB vs. HBase vs. IBM Db2 warehouse vs. SAP SQL Anywhere vs. VoltDB

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.

Wide-column store based on Apache Hadoop and on concepts of BigTable

Cloud-based data warehousing service

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store

Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

couchdb.apache.org

hbase.apache.org

www.ibm.com/products/db2/warehouse

www.sap.com/products/technology-platform/sql-anywhere.html

www.voltdb.com

Technical documentation

docs.couchdb.org/en/stable

hbase.apache.org/book.html

help.sap.com/docs/SAP_SQL_Anywhere

docs.voltdb.com

Developer

Apache Software Foundation

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

Apache Software Foundation

Apache top-level project, originally developed by Powerset

IBM

SAP

formerly Sybase

VoltDB Inc.

Initial release

2005

2008

2014

1992

2010

Current release

3.3.3, December 2023

2.3.4, January 2021

17, July 2015

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache version 2

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Erlang

Java

Java, C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
Unix
Windows

using Cygwin

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X

for development

Data scheme

schema-free

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

options to bring your own types, AVRO

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.

Import/export of XML data possible

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

RESTful HTTP/JSON API

Java API
RESTful HTTP API
Thrift

.NET Client API
JDBC
ODBC
OLE DB

ADO.NET
HTTP API
JDBC
ODBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

C
C#
C++
Groovy
Java
PHP
Python
Scala

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

View functions in JavaScript

yes

Coprocessors in Java

PL/SQL, SQL PL

yes, in C/C++, Java, .Net or Perl

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Source-replica replication

Database mirroring

Multi-source replication
Source-replica replication

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 or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

atomic operations within a single document possible

Single row ACID (across millions of columns)

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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 Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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