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DBMS > etcd vs. InfluxDB vs. OpenQM vs. TimescaleDB

System Properties Comparison etcd vs. InfluxDB vs. OpenQM vs. TimescaleDB

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonInfluxDB  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionA distributed reliable key-value storeDBMS for storing time series, events and metricsQpenQM is a high-performance, self-tuning, multi-value DBMSA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelKey-value storeTime Series DBMSMultivalue DBMSTime Series DBMS
Secondary database modelsSpatial DBMS infowith GEO packageRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.96
Rank#55  Overall
#6  Key-value stores
Score30.25
Rank#28  Overall
#1  Time Series DBMS
Score0.43
Rank#276  Overall
#10  Multivalue DBMS
Score4.76
Rank#82  Overall
#5  Time Series DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
www.influxdata.com/­products/­influxdb-overviewwww.openqm.comwww.timescale.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.influxdata.com/­influxdbwww.openqm.com/­support/­documentationdocs.timescale.com
DeveloperMartin PhillipsTimescale
Initial release201319932017
Current release3.4, August 20192.5.1, November 20223.4-122.6.0, February 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMIT-License; commercial enterprise version availableOpen Source infoGPLv2, extended commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoGoC
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Linux
OS X infothrough Homebrew
AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyes infowith some exceptionsyes
Typing infopredefined data types such as float or datenoNumeric data and Stringsnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyesyes
Secondary indexesnonoyesyes
SQL infoSupport of SQLnoSQL-like query languagenoyes infofull PostgreSQL SQL syntax
APIs and other access methodsgRPC
JSON over HTTP
HTTP API
JSON over UDP
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
Basic
C
Java
Objective C
PHP
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoyesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyes, watching key changesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoin enterprise version onlyyesyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.selectable replication factor infoin enterprise version onlyyesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoDepending on used storage engineno
User concepts infoAccess controlnosimple rights management via user accountsAccess rights can be defined down to the item levelfine grained access rights according to SQL-standard
More information provided by the system vendor
etcdInfluxDBOpenQM infoalso called QMTimescaleDB
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Timescale is the creator of TimescaleDB , the first open-source relational database...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
TimescaleDB is purpose-built to scale and handle time-series data workloads and is...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Time-series Analytics TimescaleDB boosts the performance of PostgreSQL for time-series...
» more
Key customersInfluxData has more than 1,300 paying customers, including customers include MuleSoft,...
» more
TransferWise, Maersk, Walmart, Comcast, LaunchDarkly, IBM, NOV, Cisco, Nutanix, Warner...
» more
Market metricsFastest-growing database to drive 24,500 GitHub stars Over 600,000 daily active instances
» more
With over 12,700 GitHub stars and growing, 1,000,000 active databases, and an active...
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
TimescaleDB is available as a self-hosted product under two licenses, the Timescale...
» more

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

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More resources
etcdInfluxDBOpenQM infoalso called QMTimescaleDB
DB-Engines blog posts

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

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

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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