DBMS > EJDB vs. OpenTSDB vs. Prometheus vs. RRDtool vs. TimescaleDB

System Properties Comparison EJDB vs. OpenTSDB vs. Prometheus vs. RRDtool vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Scalable Time Series DBMS based on HBase

Open-source TimeSeries DBMS and monitoring system

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

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

Primary database model

Document store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.26
Rank	#264	Overall
	#38	Document stores

Score	2.35
Rank	#113	Overall
	#8	Time Series DBMS

Score	5.71
Rank	#64	Overall
	#3	Time Series DBMS

Score	3.19
Rank	#97	Overall
	#5	Time Series DBMS

Score	2.93
Rank	#102	Overall
	#6	Time Series DBMS

Website

ejdb.org

opentsdb.net

prometheus.io

oss.oetiker.ch/rrdtool

www.timescale.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

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

prometheus.io/docs

oss.oetiker.ch/rrdtool/doc

docs.timescale.com

Developer

Softmotions

currently maintained by Yahoo and other contributors

Tobias Oetiker

Timescale

Initial release

2012

2011

2015

1999

2017

Current release

1.7.2, May 2019

License

Commercial or Open Source

Open Source

GPLv2

Open Source

LGPL

Open Source

Apache 2.0

Open Source

GPL V2 and FLOSS

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

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

server-less

Linux
Windows

HP-UX
Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

numeric data for metrics, strings for tags

Numeric data only

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.

Import of XML data possible

Exporting into and restoring from XML files possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

full PostgreSQL SQL syntax

APIs and other access methods

in-process shared library

HTTP API
Telnet API

RESTful HTTP/JSON API

in-process shared library
Pipes

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

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Erlang
Go
Java
Python
R
Ruby

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

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

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

none

Sharding

based on HBase

Sharding

none

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

yes

by Federation

none

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

none

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

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 Locking

yes

by using the rrdcached daemon

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

More information provided by the system vendor

Specific characteristics

Timescale is the creator of TimescaleDB , the first open-source relational database...
» more

Competitive advantages

TimescaleDB is purpose-built to scale and handle time-series data workloads and is...
» more

Typical application scenarios

DevOps and Infrastructure Monitoring All monitoring data is time-series data. Efficiently...
» more

Key customers

TransferWise, Maersk, AppDynamics, Walmart, Comcast, LaunchDarkly, IBM, NOV, Cisco,...
» more

Market metrics

With over 9,000 GitHub stars and growing, 600,000 active databases, and an active...
» more

Licensing and pricing models

TimescaleDB comes in 3 versions, including fully managed Cloud-hosted solutions*,...
» more

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