DBMS > Couchbase vs. IBM Db2 vs. Kdb vs. OpenEdge

System Properties Comparison Couchbase vs. IBM Db2 vs. Kdb vs. OpenEdge

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

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

High performance Time Series DBMS

Application development environment with integrated database management system

Primary database model

Document store

Relational DBMS

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

Time Series DBMS
Vector DBMS

Relational DBMS

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

Document store
RDF store

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

with Db2 Spatial Extender

Relational DBMS

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

Score	16.74
Rank	#33	Overall
	#5	Document stores

Score	123.05
Rank	#9	Overall
	#6	Relational DBMS

Score	7.73
Rank	#45	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	3.69
Rank	#78	Overall
	#42	Relational DBMS

Website

www.couchbase.com

www.ibm.com/products/db2

kx.com

www.progress.com/openedge

Technical documentation

docs.couchbase.com

www.ibm.com/docs/en/db2

code.kx.com

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Couchbase, Inc.

IBM

Kx Systems, a division of First Derivatives plc

Progress Software Corporation

Initial release

2011

1983

host version

2000

kdb was released 2000, kdb+ in 2003

1984

Current release

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

12.1, October 2016

3.6, May 2018

OpenEdge 12.2, March 2020

License

Commercial or Open Source

Open Source

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

commercial

free version is available

commercial

free 32-bit version

commercial

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 and C++

Server operating systems

Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

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.

yes

Secondary indexes

yes

table attribute 'grouped'

yes

SQL

Support of SQL

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

yes

SQL-like query language (q)

yes

close to SQL 92

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
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

JDBC
ODBC

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

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

yes

user defined functions

yes

Triggers

yes

via the TAP protocol

yes

with views

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

only with Windows/Unix/Linux Version

horizontal partitioning

since Version 11.4

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

yes

with separate tools (MQ, InfoSphere)

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

similar paradigm used for internal processing

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

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.

fine grained access rights according to SQL-standard

rights management via user accounts

Users and groups

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

Licensing and pricing models

upon request
» more

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.