DBMS > BigObject vs. eXtremeDB vs. IBM Db2 warehouse vs. Infobright vs. KairosDB

System Properties Comparison BigObject vs. eXtremeDB vs. IBM Db2 warehouse vs. Infobright vs. KairosDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Natively in-memory DBMS with options for persistency, high-availability and clustering

Cloud-based data warehousing service

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

Distributed Time Series DBMS based on Cassandra or H2

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Website

bigobject.io

www.mcobject.com

www.ibm.com/products/db2/warehouse

ignitetech.com/softwarelibrary/infobrightdb

github.com/kairosdb/kairosdb

Technical documentation

docs.bigobject.io

www.mcobject.com/docs/extremedb.htm

kairosdb.github.io

Developer

BigObject, Inc.

McObject

IBM

Ignite Technologies Inc.; formerly InfoBright Inc.

Initial release

2015

2001

2014

2005

2013

Current release

8.2, 2021

1.2.2, November 2018

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

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++

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)

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

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.

support of XML interfaces available

Import/export of XML data possible

Secondary indexes

yes

Knowledge Grid Technology used instead

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with the option: eXtremeSQL

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

.NET Client API
JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

.Net
C
C#
C++
Java
Lua
Python
Scala

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

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

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Lua

yes

PL/SQL, SQL PL

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning / sharding

Sharding

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

none

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes

Source-replica replication

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

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

Optimistic (MVCC) and pessimistic (locking) strategies available

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

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more

Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more

Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more

Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
» more

Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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