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DBMS > DataFS vs. InfluxDB vs. JaguarDB vs. Vitess

System Properties Comparison DataFS vs. InfluxDB vs. JaguarDB vs. Vitess

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Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonInfluxDB  Xexclude from comparisonJaguarDB  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.DBMS for storing time series, events and metricsPerformant, highly scalable DBMS for AI and IoT applicationsScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelObject oriented DBMSTime Series DBMSKey-value store
Vector DBMS
Relational DBMS
Secondary database modelsGraph DBMSSpatial DBMS infowith GEO packageDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score25.83
Rank#28  Overall
#1  Time Series DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitenewdatabase.comwww.influxdata.com/­products/­influxdb-overviewwww.jaguardb.comvitess.io
Technical documentationdev.mobiland.com/­Overview.xspdocs.influxdata.com/­influxdbwww.jaguardb.com/­support.htmlvitess.io/­docs
DeveloperMobiland AGDataJaguar, Inc.The Linux Foundation, PlanetScale
Initial release2018201320152013
Current release1.1.263, October 20222.7.6, April 20243.3 July 202315.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoGPL V3.0Open Source infoApache Version 2.0, commercial licenses available
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 languageGoC++ infothe server part. Clients available in other languagesGo
Server operating systemsWindowsLinux
OS X infothrough Homebrew
LinuxDocker
Linux
macOS
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-freeyesyes
Typing infopredefined data types such as float or dateyesNumeric data and Stringsyesyes
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.nonono
Secondary indexesnonoyesyes
SQL infoSupport of SQLnoSQL-like query languageA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersyes infowith proprietary extensions
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
HTTP API
JSON over UDP
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languages.Net
C
C#
C++
VB.Net
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
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 proceduresnonoyes infoproprietary syntax
Triggersno, except callback-events from server when changes happenednonoyes
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemSharding infoin enterprise version onlyShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infoin enterprise version onlyMulti-source replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesnonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes 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.noyes infoDepending on used storage enginenoyes
User concepts infoAccess controlWindows-Profilesimple rights management via user accountsrights management via user accountsUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
DataFSInfluxDBJaguarDBVitess
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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More resources
DataFSInfluxDBJaguarDBVitess
DB-Engines blog posts

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

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4 July 2016, Matthias Gelbmann

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Recent citations in the news

Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services
14 March 2024, AWS Blog

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

Time-series database startup InfluxData debuts self-managed version of InfluxDB
6 September 2023, SiliconANGLE News

provided by Google News

Vitess, the database clustering system powering YouTube, graduates CNCF incubation
5 November 2019, SiliconANGLE 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

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

provided by Google News



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