DBMS > IBM Db2 Event Store vs. KairosDB vs. Linter vs. openGauss vs. SAP HANA

System Properties Comparison IBM Db2 Event Store vs. KairosDB vs. Linter vs. openGauss vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Distributed Time Series DBMS based on Cassandra or H2

RDBMS for high security requirements

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Event Store
Time Series DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

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

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

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

github.com/kairosdb/kairosdb

linter.ru

gitee.com/opengauss
opengauss.org

www.sap.com/products/hana.html

Technical documentation

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

kairosdb.github.io

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

help.sap.com/hana

Developer

IBM

relex.ru

Huawei and openGauss community

SAP

Initial release

2017

2013

1990

2019

2010

Current release

2.0

1.2.2, November 2018

3.0, March 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Apache 2.0

commercial

Open Source

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

Java

C and C++

C, C++, Java

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux

Appliance or cloud-service

Data scheme

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

ANSI SQL 2011

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

JDBC
ODBC

Supported programming languages

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

Java
JavaScript

Node.js
PHP
Python

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C
C++
Java

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

horizontal partitioning (by range, list and hash)

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

selectable replication factor

based on Cassandra

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

No - written data is immutable

yes

Durability

Support for making data persistent

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

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

fine grained access rights according to SQL-standard

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

yes

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