DBMS > FatDB vs. IBM Db2 Event Store vs. Infobright vs. OpenTSDB

System Properties Comparison FatDB vs. IBM Db2 Event Store vs. Infobright vs. OpenTSDB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Distributed Event Store optimized for Internet of Things use cases

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

Scalable Time Series DBMS based on HBase

Primary database model

Document store
Key-value store

Event Store
Time Series DBMS

Relational DBMS

Time Series DBMS

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

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Website

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

ignitetech.com/softwarelibrary/infobrightdb

opentsdb.net

Technical documentation

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

opentsdb.net/docs/build/html/index.html

Developer

FatCloud

IBM

Ignite Technologies Inc.; formerly InfoBright Inc.

currently maintained by Yahoo and other contributors

Initial release

2012

2017

2005

2011

Current release

2.0

License

Commercial or Open Source

commercial

free developer edition available

commercial

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

Open Source

LGPL

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++

Java

Server operating systems

Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

SQL

Support of SQL

Via inetgration in SQL Server

yes

through the embedded Spark runtime

yes

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

HTTP API
Telnet API

Supported programming languages

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

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

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

yes

via applications

yes

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Active-active shard replication

Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

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

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
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