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DBMS > InfluxDB vs. Oracle NoSQL vs. RocksDB vs. Vitess

System Properties Comparison InfluxDB vs. Oracle NoSQL vs. RocksDB vs. Vitess

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Editorial information provided by DB-Engines
NameInfluxDB  Xexclude from comparisonOracle NoSQL  Xexclude from comparisonRocksDB  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionDBMS for storing time series, events and metricsA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodesEmbeddable persistent key-value store optimized for fast storage (flash and RAM)Scalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelTime Series DBMSDocument store
Key-value store
Relational DBMS
Key-value storeRelational DBMS
Secondary database modelsSpatial DBMS infowith GEO packageDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score25.83
Rank#28  Overall
#1  Time Series DBMS
Score2.95
Rank#100  Overall
#17  Document stores
#17  Key-value stores
#50  Relational DBMS
Score3.65
Rank#85  Overall
#11  Key-value stores
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitewww.influxdata.com/­products/­influxdb-overviewwww.oracle.com/­database/­nosql/­technologies/­nosqlrocksdb.orgvitess.io
Technical documentationdocs.influxdata.com/­influxdbdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.htmlgithub.com/­facebook/­rocksdb/­wikivitess.io/­docs
DeveloperOracleFacebook, Inc.The Linux Foundation, PlanetScale
Initial release2013201120132013
Current release2.7.6, April 202423.3, December 20238.11.4, April 202415.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)Open Source infoBSDOpen 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 languageGoJavaC++Go
Server operating systemsLinux
OS X infothrough Homebrew
Linux
Solaris SPARC/x86
LinuxDocker
Linux
macOS
Data schemeschema-freeSupport Fixed schema and Schema-less deployment with the ability to interoperate between them.schema-freeyes
Typing infopredefined data types such as float or dateNumeric data and Stringsoptionalnoyes
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 indexesnoyesnoyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsnoyes infowith proprietary extensions
APIs and other access methodsHTTP API
JSON over UDP
RESTful HTTP APIC++ API
Java API
ADO.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
C
C#
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
Perl
Python
Ruby
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 proceduresnononoyes infoproprietary syntax
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoin enterprise version onlyShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infoin enterprise version onlyElectable source-replica replication per shard. Support distributed global deployment with Multi-region table featureyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infodepending on configuration
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynononoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoconfigurable infoACID within a storage node (=shard)yesACID 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.yes infoDepending on used storage engineyes infooff heap cacheyesyes
User concepts infoAccess controlsimple rights management via user accountsAccess rights for users and rolesnoUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
InfluxDBOracle NoSQLRocksDBVitess
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.

Related products and services
3rd partiesSpeedb: A high performance RocksDB-compliant key-value store optimized for write-intensive workloads.
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More resources
InfluxDBOracle NoSQLRocksDBVitess
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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Recent citations in the news

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