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DBMS > InfluxDB vs. PlanetScale vs. SiriDB vs. Vitess

System Properties Comparison InfluxDB vs. PlanetScale vs. SiriDB vs. Vitess

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Editorial information provided by DB-Engines
NameInfluxDB  Xexclude from comparisonPlanetScale  Xexclude from comparisonSiriDB  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionDBMS for storing time series, events and metricsScalable, distributed, serverless MySQL database platform built on top of VitessOpen Source Time Series DBMSScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS infowith GEO packageDocument store
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score24.39
Rank#28  Overall
#1  Time Series DBMS
Score1.49
Rank#155  Overall
#72  Relational DBMS
Score0.07
Rank#378  Overall
#42  Time Series DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitewww.influxdata.com/­products/­influxdb-overviewplanetscale.comsiridb.comvitess.io
Technical documentationdocs.influxdata.com/­influxdbplanetscale.com/­docsdocs.siridb.comvitess.io/­docs
DeveloperPlanetScaleCesbitThe Linux Foundation, PlanetScale
Initial release2013202020172013
Current release2.7.6, April 202415.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoMIT-License; commercial enterprise version availablecommercialOpen Source infoMIT LicenseOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoGoCGo
Server operating systemsLinux
OS X infothrough Homebrew
Docker
Linux
macOS
LinuxDocker
Linux
macOS
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateNumeric data and Stringsyesyes infoNumeric datayes
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.nono
Secondary indexesnoyesyesyes
SQL infoSupport of SQLSQL-like query languageyes infowith proprietary extensionsnoyes infowith proprietary extensions
APIs and other access methodsHTTP API
JSON over UDP
ADO.NET
JDBC
MySQL protocol
ODBC
HTTP APIADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languages.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes infoproprietary syntaxnoyes infoproprietary syntax
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoin enterprise version onlyShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infoin enterprise version onlyMulti-source replication
Source-replica replication
yesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency across shards
Immediate Consistency within a shard
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyes infonot for MyISAM storage enginenoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at shard levelnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyes infotable locks or row locks depending on storage engineyesyes infotable locks or row locks depending on storage engine
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.yes infoDepending on used storage engineyesyesyes
User concepts infoAccess controlsimple rights management via user accountsUsers with fine-grained authorization concept infono user groups or rolessimple rights management via user accountsUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
InfluxDBPlanetScaleSiriDBVitess
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
News

Scaling Data Collection: Solving Renewable Energy Challenges with InfluxDB
6 June 2024

Deadman Alerts with Grafana and InfluxDB Cloud 3.0
5 June 2024

Chasing the Skies: Monitoring Flights with InfluxDB
4 June 2024

Monitoring Your Cloud Environments and Applications with InfluxDB
30 May 2024

Webinar Recap: Unleash the Full Potential of Your Time Series Data with InfluxDB and AWS
29 May 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources
InfluxDBPlanetScaleSiriDBVitess
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

show all

Recent citations in the news

Amazon Timestream for InfluxDB is now generally available
15 March 2024, AWS Blog

Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB?
5 June 2024, hackernoon.com

Amazon Timestream: Managed InfluxDB for Time Series Data
14 March 2024, The New Stack

InfluxData Collaborating with AWS to Bring InfluxDB and Time Series Analytics to Developers Around the World
14 March 2024, Business Wire

How the FDAP Stack Gives InfluxDB 3.0 Real-Time Speed, Efficiency
15 March 2024, Datanami

provided by Google News

PlanetScale ends free tier bid, sheds staff in profitability bid
11 March 2024, The Register

PlanetScale forks MySQL to add vector support
3 October 2023, TechCrunch

PlanetScale Named to Fortune 2023 Best Small Workplaces
31 August 2023, businesswire.com

PlanetScale review: Horizontally scalable MySQL in the cloud
1 September 2021, InfoWorld

How to Migrate to PlanetScale's Serverless Database
14 October 2021, The New Stack

provided by Google News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

provided by Google News



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