DBMS > OpenTSDB vs. Oracle vs. Prometheus vs. SiteWhere vs. TimescaleDB

System Properties Comparison OpenTSDB vs. Oracle vs. Prometheus vs. SiteWhere vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Scalable Time Series DBMS based on HBase

Widely used RDBMS

Open-source Time Series DBMS and monitoring system

M2M integration platform for persisting/querying time series data

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

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Relational DBMS

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

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

opentsdb.net

www.oracle.com/database

prometheus.io

github.com/sitewhere/sitewhere

www.timescale.com

Technical documentation

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

docs.oracle.com/en/database

prometheus.io/docs

sitewhere1.sitewhere.io/index.html

docs.timescale.com

Developer

currently maintained by Yahoo and other contributors

Oracle

SiteWhere

Timescale

Initial release

2011

1980

2015

2010

2017

Current release

23c, September 2023

2.15.0, May 2024

License

Commercial or Open Source

Open Source

LGPL

commercial

restricted free version is available

Open Source

Apache 2.0

Open Source

Common Public Attribution License Version 1.0

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

C and C++

Java

Server operating systems

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

yes

predefined scheme

yes

Typing

predefined data types such as float or date

numeric data for metrics, strings for tags

yes

Numeric data only

yes

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

Import of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

full PostgreSQL SQL syntax

APIs and other access methods

HTTP API
Telnet API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

RESTful HTTP/JSON API

HTTP REST

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

Supported programming languages

Erlang
Go
Java
Python
R
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Sharding, horizontal partitioning

Sharding

based on HBase

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on HBase

Multi-source replication
Source-replica replication

yes

by Federation

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

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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