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DBMS > ReductStore vs. Valentina Server vs. Vitess

System Properties Comparison ReductStore vs. Valentina Server vs. Vitess

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Editorial information provided by DB-Engines
NameReductStore  Xexclude from comparisonValentina Server  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.Object-relational database and reports serverScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Score0.21
Rank#325  Overall
#144  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitegithub.com/­reductstore
www.reduct.store
www.valentina-db.netvitess.io
Technical documentationwww.reduct.store/­docsvalentina-db.com/­docs/­dokuwiki/­v5/­doku.phpvitess.io/­docs
DeveloperReductStore LLCParadigma SoftwareThe Linux Foundation, PlanetScale
Initial release202319992013
Current release1.9, March 20245.7.515.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoBusiness Source License 1.1commercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, RustGo
Server operating systemsDocker
Linux
macOS
Windows
Linux
OS X
Windows
Docker
Linux
macOS
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
Secondary indexesyesyes
SQL infoSupport of SQLyesyes infowith proprietary extensions
APIs and other access methodsHTTP APIODBCADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC++
JavaScript (Node.js)
Python
Rust
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
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 proceduresyesyes infoproprietary syntax
Triggersyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at shard level
Concurrency infoSupport for concurrent manipulation of datayes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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More resources
ReductStoreValentina ServerVitess
Recent citations in the news

A Look at Valentina — SitePoint
18 April 2014, SitePoint

MySQL GUI Tools for Windows and Ubuntu/Linux: Top 8 free or open source
7 December 2018, H2S Media

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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