DBMS > IBM Db2 Event Store vs. mSQL vs. OrigoDB vs. Sequoiadb vs. Transbase

System Properties Comparison IBM Db2 Event Store vs. mSQL vs. OrigoDB vs. Sequoiadb vs. Transbase

Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

NewSQL database with distributed OLTP and SQL

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Document store
Object oriented DBMS

Document store
Relational DBMS

Relational DBMS

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

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

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

hughestech.com.au/products/msql

origodb.com

www.sequoiadb.com

www.transaction.de/en/products/transbase.html

Technical documentation

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

origodb.com/docs

www.sequoiadb.com/en/index.php?m=Files&a=index

www.transaction.de/en/products/transbase/features.html

Developer

IBM

Hughes Technologies

Robert Friberg et al

Sequoiadb Ltd.

Transaction Software GmbH

Initial release

2017

1994

2009

under the name LiveDB

2013

1987

Current release

2.0

4.4, October 2021

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

free developer edition available

commercial

free licenses can be provided

Open Source

Server: AGPL; Client: Apache V2

commercial

free development license

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++

C++

C and C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
Windows

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

yes

oid, date, timestamp, binary, regex

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like query language

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

.NET Client API
HTTP API
LINQ

proprietary protocol using JSON

ADO.NET
JDBC
ODBC
Proprietary native 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++
Delphi
Java
Perl
PHP
Tcl

.Net

.Net
C++
Java
PHP
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

JavaScript

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

depending on model

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Document is locked during a transaction

yes

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

Write ahead log

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

Role based authorization

simple password-based access control

fine grained access rights according to SQL-standard

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Advancements in streaming data storage, real-time analysis and machine learning
25 July 2019, IBM

IBM Builds New Ultra-Fast Platform for Hoovering Up and Analyzing Data from Anywhere
31 May 2018, Data Center Knowledge

How IBM Is Turning Db2 into an 'AI Database'
3 June 2019, Datanami

Best cloud databases of 2022
4 October 2022, ITPro

Why a robust data management strategy is essential today | IBM HDM
19 September 2019, Express Computer

provided by Google News

Make Your MySQL Server More Secure With These 7 Steps - MUO
1 December 2022, MakeUseOf

Writing a Web Service in Perl
9 July 2003, PCQuest

provided by Google News

Share this page