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DBMS > Graph Engine vs. InfluxDB vs. SQLite vs. TempoIQ vs. Valentina Server

System Properties Comparison Graph Engine vs. InfluxDB vs. SQLite vs. TempoIQ vs. Valentina Server

Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonInfluxDB  Xexclude from comparisonSQLite  Xexclude from comparisonTempoIQ infoformerly TempoDB  Xexclude from comparisonValentina Server  Xexclude from comparison
TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.
DescriptionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineDBMS for storing time series, events and metricsWidely used embeddable, in-process RDBMSScalable analytics DBMS for sensor data, provided as a service (SaaS)Object-relational database and reports server
Primary database modelGraph DBMS
Key-value store
Time Series DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score24.39
Rank#28  Overall
#1  Time Series DBMS
Score111.41
Rank#10  Overall
#7  Relational DBMS
Score0.21
Rank#325  Overall
#144  Relational DBMS
Websitewww.graphengine.iowww.influxdata.com/­products/­influxdb-overviewwww.sqlite.orgtempoiq.com (offline)www.valentina-db.net
Technical documentationwww.graphengine.io/­docs/­manualdocs.influxdata.com/­influxdbwww.sqlite.org/­docs.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperMicrosoftDwayne Richard HippTempoIQParadigma Software
Initial release20102013200020121999
Current release2.7.6, April 20243.46.0  (23 May 2024), May 20245.7.5
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoPublic Domaincommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation language.NET and CGoC
Server operating systems.NETLinux
OS X infothrough Homebrew
server-lessLinux
OS X
Windows
Data schemeyesschema-freeyes infodynamic column typesschema-freeyes
Typing infopredefined data types such as float or dateyesNumeric data and Stringsyes infonot rigid because of 'dynamic typing' concept.yesyes
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.nononono
Secondary indexesnoyesyes
SQL infoSupport of SQLnoSQL-like query languageyes infoSQL-92 is not fully supportednoyes
APIs and other access methodsRESTful HTTP APIHTTP API
JSON over UDP
ADO.NET infoinofficial driver
JDBC infoinofficial driver
ODBC infoinofficial driver
HTTP APIODBC
Supported programming languagesC#
C++
F#
Visual Basic
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl
C#
Java
JavaScript infoNode.js
Python
Ruby
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresyesnononoyes
Triggersnonoyesyes infoRealtime Alertsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoin enterprise version onlynone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infoin enterprise version onlynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infovia file-system locksyes
Durability infoSupport for making data persistentoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoDepending on used storage engineyesnoyes
User concepts infoAccess controlsimple rights management via user accountsnosimple authentication-based access controlfine grained access rights according to SQL-standard
More information provided by the system vendor
Graph Engine infoformer name: TrinityInfluxDBSQLiteTempoIQ infoformerly TempoDBValentina Server
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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3rd partiesNavicat for SQLite is a powerful and comprehensive SQLite GUI that provides a complete set of functions for database management and development.
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We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Graph Engine infoformer name: TrinityInfluxDBSQLiteTempoIQ infoformerly TempoDBValentina Server
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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Big gains for Relational Database Management Systems in DB-Engines Ranking
2 February 2016, Matthias Gelbmann

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