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DBMS > GridGain vs. Prometheus vs. Spark SQL vs. Transbase

System Properties Comparison GridGain vs. Prometheus vs. Spark SQL vs. Transbase

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonPrometheus  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteOpen-source Time Series DBMS and monitoring systemSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelKey-value store
Relational DBMS
Time Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitewww.gridgain.comprometheus.iospark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationwww.gridgain.com/­docs/­index.htmlprometheus.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperGridGain Systems, Inc.Apache Software FoundationTransaction Software GmbH
Initial release2007201520141987
Current releaseGridGain 8.5.13.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0commercial infofree development license
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 languageJava, C++, .NetGoScalaC and C++
Server operating systemsLinux
OS X
Solaris
Windows
Linux
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesNumeric data onlyyesyes
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.yesno infoImport of XML data possiblenono
Secondary indexesyesnonoyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnoSQL-like DML and DDL statementsyes
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
RESTful HTTP/JSON APIJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)nonoyes
Triggersyes (cache interceptors and events)nonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yes infoby FederationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoyes
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.yesnonono
User concepts infoAccess controlSecurity Hooks for custom implementationsnonofine grained access rights according to SQL-standard

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More resources
GridGainPrometheusSpark SQLTransbase
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