DBMS > BigObject vs. Infobright vs. KairosDB vs. Riak TS vs. Trafodion

System Properties Comparison BigObject vs. Infobright vs. KairosDB vs. Riak TS vs. Trafodion

Editorial information provided by DB-Engines

Name

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

Description

Analytic DBMS for real-time computations and queries

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Distributed Time Series DBMS based on Cassandra or H2

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

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

bigobject.io

ignitetech.com/softwarelibrary/infobrightdb

github.com/kairosdb/kairosdb

trafodion.apache.org

Technical documentation

docs.bigobject.io

kairosdb.github.io

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

trafodion.apache.org/documentation.html

Developer

BigObject, Inc.

Ignite Technologies Inc.; formerly InfoBright Inc.

Open Source, formerly Basho Technologies

Apache Software Foundation, originally developed by HP

Initial release

2015

2005

2013

2015

2014

Current release

1.2.2, November 2018

3.0.0, September 2022

2.3.0, February 2019

License

Commercial or Open Source

commercial

free community edition available

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Apache 2.0

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

Java

Erlang

C++, Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
Windows

Linux
OS X
Windows

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

yes

Knowledge Grid Technology used instead

restricted

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

yes, limited

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

HTTP API
Native Erlang Interface

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java
JavaScript

Node.js
PHP
Python

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

Lua

Erlang

Java Stored Procedures

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

selectable replication factor

based on Cassandra

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

none

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

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

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

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

exploiting MySQL or PostgreSQL frontend capabilities

simple password-based access control

fine grained access rights according to SQL-standard

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