DBMS > IBM Db2 Event Store vs. Machbase Neo vs. SAP IQ vs. Transwarp KunDB

System Properties Comparison IBM Db2 Event Store vs. Machbase Neo vs. SAP IQ vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

TimeSeries DBMS for AIoT and BigData

Columnar RDBMS optimized for Big Data analytics

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Event Store
Time Series DBMS

Time Series DBMS

Relational DBMS

column-oriented

Relational DBMS

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

Score	0.23
Rank	#316	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.22
Rank	#324	Overall
	#29	Time Series DBMS

Score	3.27
Rank	#96	Overall
	#50	Relational DBMS

Score	0.14
Rank	#340	Overall
	#148	Relational DBMS

Website

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

machbase.com

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.transwarp.cn/en/product/kundb

Technical documentation

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

machbase.com/dbms

help.sap.com/docs/SAP_IQ

Developer

IBM

Machbase

SAP, formerly Sybase

Transwarp

Initial release

2017

2013

1994

Current release

2.0

V8.0, August 2023

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

free developer edition available

commercial

free test version available

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 and C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

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

SQL-like query language

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

selectable replication factor

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

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

volatile and lookup table

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

yes

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