DBMS > IBM Db2 Event Store vs. TempoIQ vs. Trafodion vs. Valentina Server

System Properties Comparison IBM Db2 Event Store vs. TempoIQ vs. Trafodion vs. Valentina Server

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Distributed Event Store optimized for Internet of Things use cases

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Transactional SQL-on-Hadoop DBMS

Object-relational database and reports server

Primary database model

Event Store
Time Series DBMS

Time Series 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	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

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

tempoiq.com (offline)

trafodion.apache.org

www.valentina-db.net

Technical documentation

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

trafodion.apache.org/documentation.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

IBM

TempoIQ

Apache Software Foundation, originally developed by HP

Paradigma Software

Initial release

2017

2012

2014

1999

Current release

2.0

2.3.0, February 2019

5.7.5

License

Commercial or Open Source

commercial

free developer edition available

commercial

Open Source

Apache 2.0

commercial

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 and C++

C++, Java

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux

Linux
OS X
Windows

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

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP API

ADO.NET
JDBC
ODBC

ODBC

Supported programming languages

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

C#
Java
JavaScript

Node.js
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes

Triggers

yes

Realtime Alerts

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

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

User concepts

Access control

fine grained access rights according to SQL-standard

simple authentication-based access control

fine grained access rights according to SQL-standard

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