DBMS > IBM Db2 warehouse vs. openGauss vs. RRDtool vs. SAP SQL Anywhere vs. SQLite

System Properties Comparison IBM Db2 warehouse vs. openGauss vs. RRDtool vs. SAP SQL Anywhere vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Cloud-based data warehousing service

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

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

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.ibm.com/products/db2/warehouse

gitee.com/opengauss
opengauss.org

oss.oetiker.ch/rrdtool

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

www.sqlite.org

Technical documentation

docs.opengauss.org/en
gitee.com/opengauss/docs

oss.oetiker.ch/rrdtool/doc

help.sap.com/docs/SAP_SQL_Anywhere

www.sqlite.org/docs.html

Developer

IBM

Huawei and openGauss community

Tobias Oetiker

SAP

formerly Sybase

Dwayne Richard Hipp

Initial release

2014

2019

1999

1992

2000

Current release

3.0, March 2022

1.8.0, 2022

17, July 2015

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

GPL V2 and FLOSS

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, C++, Java

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

hosted

Linux

HP-UX
Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

server-less

Data scheme

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import/export of XML data possible

Exporting into and restoring from XML files possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL 2011

yes

SQL-92 is not fully supported

APIs and other access methods

.NET Client API
JDBC
ODBC
OLE DB

JDBC
ODBC

in-process shared library
Pipes

ADO.NET
HTTP API
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

C
C++
Java

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

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

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

PL/SQL, SQL PL

yes

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash)

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

none

Source-replica replication

Database mirroring

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

by using the rrdcached daemon

yes

via file-system locks

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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