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DBMS > Cachelot.io vs. Fujitsu Enterprise Postgres vs. GridDB vs. Spark SQL

System Properties Comparison Cachelot.io vs. Fujitsu Enterprise Postgres vs. GridDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameCachelot.io  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGridDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionIn-memory caching systemEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.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 modelKey-value storeRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#383  Overall
#60  Key-value stores
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitecachelot.iowww.postgresql.fastware.comgriddb.netspark.apache.org/­sql
Technical documentationwww.postgresql.fastware.com/­product-manualsdocs.griddb.netspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyToshiba CorporationApache Software Foundation
Initial release201520132014
Current releaseFujitsu Enterprise Postgres 14, January 20225.1, August 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoSimplified BSD LicensecommercialOpen 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 servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++CC++Scala
Server operating systemsFreeBSD
Linux
OS X
Linux
Windows
LinuxLinux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyes 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.nonono
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoyesSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statements
APIs and other access methodsMemcached protocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsnono
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesnonepartitioning by range, list and by hashShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationSource-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 systemnoneImmediate ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.noyesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users can be defined per databaseno
More information provided by the system vendor
Cachelot.ioFujitsu Enterprise PostgresGridDBSpark SQL
Specific characteristics100% compatible with community PostgreSQL
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Factory 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 metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
GitHub trending repository
» more
Licensing and pricing modelsCore based licensing
» more
Open 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.ioFujitsu Enterprise PostgresGridDBSpark SQL
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