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DBMS > Cachelot.io vs. GridDB vs. Spark SQL vs. Vitess

System Properties Comparison Cachelot.io vs. GridDB vs. Spark SQL vs. Vitess

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Editorial information provided by DB-Engines
NameCachelot.io  Xexclude from comparisonGridDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionIn-memory caching systemScalable in-memory time series database optimized for IoT and Big DataSpark SQL is a component on top of 'Spark Core' for structured data processingScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelKey-value storeTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#383  Overall
#60  Key-value stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitecachelot.iogriddb.netspark.apache.org/­sqlvitess.io
Technical documentationdocs.griddb.netspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvitess.io/­docs
DeveloperToshiba CorporationApache Software FoundationThe Linux Foundation, PlanetScale
Initial release2015201320142013
Current release5.1, August 20223.5.0 ( 2.13), September 202315.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoSimplified BSD LicenseOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0Open 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 languageC++C++ScalaGo
Server operating systemsFreeBSD
Linux
OS X
LinuxLinux
OS X
Windows
Docker
Linux
macOS
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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 SQLnoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statementsyes infowith proprietary extensions
APIs and other access methodsMemcached protocolJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
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 proceduresnononoyes infoproprietary syntax
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency within container, eventual consistency across containersEventual 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 datanoACID at container levelnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentnoyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlnoAccess rights for users can be defined per databasenoUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
Cachelot.ioGridDBSpark SQLVitess
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» 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
Cachelot.ioGridDBSpark SQLVitess
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