DBMS > BigObject vs. FatDB vs. OpenTSDB vs. TimescaleDB

System Properties Comparison BigObject vs. FatDB vs. OpenTSDB vs. TimescaleDB

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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

Analytic DBMS for real-time computations and queries

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

Scalable Time Series DBMS based on HBase

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store
Key-value store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

bigobject.io

opentsdb.net

www.timescale.com

Technical documentation

docs.bigobject.io

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

docs.timescale.com

Developer

BigObject, Inc.

FatCloud

currently maintained by Yahoo and other contributors

Timescale

Initial release

2015

2012

2011

2017

Current release

2.15.0, May 2024

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

LGPL

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

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Windows

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

Via inetgration in SQL Server

yes

full PostgreSQL SQL syntax

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

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

HTTP API
Telnet API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Erlang
Go
Java
Python
R
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Lua

yes

via applications

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on HBase

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

Immediate Consistency

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

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

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

show all

Recent citations in the news

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

MapR to help admins peer into dense Hadoop clusters
28 June 2016, SiliconANGLE News

A real-time processing revival - O'Reilly Radar
2 April 2015, O'Reilly Radar

provided by Google News

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, Microsoft

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

provided by Google News

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