DBMS > Couchbase vs. IBM Db2 Event Store vs. IBM Db2 warehouse vs. SAP SQL Anywhere vs. StarRocks

System Properties Comparison Couchbase vs. IBM Db2 Event Store vs. IBM Db2 warehouse vs. SAP SQL Anywhere vs. StarRocks

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

Distributed Event Store optimized for Internet of Things use cases

Cloud-based data warehousing service

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

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Document store

Event Store
Time Series 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

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	0.93
Rank	#198	Overall
	#93	Relational DBMS

Website

www.couchbase.com

www.ibm.com/products/db2-event-store

www.ibm.com/products/db2/warehouse

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

www.starrocks.io

Technical documentation

docs.couchbase.com

www.ibm.com/docs/en/db2-event-store

help.sap.com/docs/SAP_SQL_Anywhere

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Couchbase, Inc.

IBM

SAP

formerly Sybase

The Linux Foundation

since Feb 2023

Initial release

2011

2017

2014

1992

2020

Current release

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

2.0

17, July 2015

2.5.3, March 2023

License

Commercial or Open Source

Open Source

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

commercial

free developer edition available

commercial

Open Source

Apache Version 2.0

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, C++, Go and Erlang

C and C++

C++, Java

Server operating systems

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

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

yes

through the embedded Spark runtime

yes

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
DB2 Connect
JDBC
ODBC
RESTful HTTP API

.NET Client API
JDBC
ODBC
OLE DB

ADO.NET
HTTP API
JDBC
ODBC

JDBC
MySQL protocol

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

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

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

Java

Server-side scripts

Stored procedures

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

yes

PL/SQL, SQL PL

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

user defined functions

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

none

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Active-active shard replication

yes

Source-replica replication

Database mirroring

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

Eventual Consistency

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

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

Role based access control and fine grained access rights

More information provided by the system vendor

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.