DBMS > IBM Db2 Event Store vs. Riak TS vs. Trafodion

System Properties Comparison IBM Db2 Event Store vs. Riak TS vs. Trafodion

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Editorial information provided by DB-Engines

Name

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Transactional SQL-on-Hadoop DBMS

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	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

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

trafodion.apache.org

Technical documentation

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

www.tiot.jp/riak-docs/riak/ts/latest

trafodion.apache.org/documentation.html

Developer

IBM

Open Source, formerly Basho Technologies

Apache Software Foundation, originally developed by HP

Initial release

2017

2015

2014

Current release

2.0

3.0.0, September 2022

2.3.0, February 2019

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Apache 2.0

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++

Erlang

C++, Java

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X

Linux

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

restricted

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes, limited

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP API
Native Erlang Interface

ADO.NET
JDBC
ODBC

Supported programming languages

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

Erlang

Java Stored Procedures

Triggers

yes

pre-commit hooks and post-commit hooks

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

selectable replication factor

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

links between datasets can be stored

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

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