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DBMS > InfluxDB vs. Sphinx

System Properties Comparison InfluxDB vs. Sphinx

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Editorial information provided by DB-Engines
NameInfluxDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionDBMS for storing time series, events and metricsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSSearch engine
Secondary database modelsSpatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score29.78
Rank#29  Overall
#1  Time Series DBMS
Score6.95
Rank#64  Overall
#8  Search engines
Websitewww.influxdata.com/­products/­influxdb-overviewsphinxsearch.com
Technical documentationdocs.influxdata.com/­influxdbsphinxsearch.com/­docs
DeveloperSphinx Technologies Inc.
Initial release20132001
Current release2.3, June 20223.4.1, July 2021
License infoCommercial or Open SourceOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++
Server operating systemsLinux
OS X infothrough Homebrew
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyes
Typing infopredefined data types such as float or dateNumeric data and Stringsno
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.no
Secondary indexesnoyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsHTTP API
JSON over UDP
Proprietary protocol
Supported programming languages.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoin enterprise version onlySharding infoPartitioning is done manually, search queries against distributed index is supported
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 methodsnono
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoDepending on used storage engine
User concepts infoAccess controlsimple rights management via user accountsno
More information provided by the system vendor
InfluxDBSphinx
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 1,300 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest growing database to drive 23,500 GitHub stars Over 600,000 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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More resources
InfluxDBSphinx
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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The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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Recent citations in the news

Visualizing Time-Series Data with ECharts and InfluxDB
12 July 2022, thenewstack.io

Obtaining and Storing Time-Series Data with Python
27 July 2022, thenewstack.io

Automate Anomaly Detection for Time Series Data – The New Stack
2 August 2022, thenewstack.io

A Way to Replicate Data at the Edge
1 August 2022, thenewstack.io

Getting Started with Python and Geo-Temporal Analysis
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