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DBMS > Citus vs. Cloudflare Workers KV vs. GridDB vs. Spark SQL

System Properties Comparison Citus vs. Cloudflare Workers KV vs. GridDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonCloudflare Workers KV  Xexclude from comparisonGridDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.Scalable in-memory time series database optimized for IoT and Big DataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value storeTime Series DBMSRelational DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score0.32
Rank#283  Overall
#40  Key-value stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.citusdata.comwww.cloudflare.com/­developer-platform/­workers-kvgriddb.netspark.apache.org/­sql
Technical documentationdocs.citusdata.comdevelopers.cloudflare.com/­kv/­apidocs.griddb.netspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCloudflareToshiba CorporationApache Software Foundation
Initial release2010201820132014
Current release8.1, December 20185.1, August 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0
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 languageCC++Scala
Server operating systemsLinuxhostedLinuxLinux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyes infonumerical, string, blob, geometry, boolean, timestampyes
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.yes infospecific XML type available, but no XML query functionalitynonono
Secondary indexesyesnoyesno
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP REST
Proprietary protocol
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nonono
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users can be defined per databaseno
More information provided by the system vendor
CitusCloudflare Workers KVGridDBSpark SQL
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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CitusCloudflare Workers KVGridDBSpark SQL
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