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DBMS > FoundationDB vs. Geode vs. Kinetica vs. Spark SQL vs. TerarkDB

System Properties Comparison FoundationDB vs. Geode vs. Kinetica vs. Spark SQL vs. TerarkDB

Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonGeode  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerarkDB  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionOrdered key-value store. Core features are complimented by layers.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processingA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Key-value storeRelational DBMSRelational DBMSKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score1.92
Rank#131  Overall
#23  Key-value stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitegithub.com/­apple/­foundationdbgeode.apache.orgwww.kinetica.comspark.apache.org/­sqlgithub.com/­bytedance/­terarkdb
Technical documentationapple.github.io/­foundationdbgeode.apache.org/­docsdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperFoundationDBOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.KineticaApache Software FoundationByteDance, originally Terark
Initial release20132002201220142016
Current release6.2.28, November 20201.1, February 20177.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses available as GemfirecommercialOpen Source infoApache 2.0commercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC, C++ScalaC++
Server operating systemsLinux
OS X
Windows
All OS with a Java VM infothe JDK (8 or later) is also requiredLinuxLinux
OS X
Windows
Data schemeschema-free infosome layers support schemasschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateno infosome layers support typingyesyesyesno
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.nononono
Secondary indexesnonoyesnono
SQL infoSupport of SQLsupported in specific SQL layer onlySQL-like query language (OQL)SQL-like DML and DDL statementsSQL-like DML and DDL statementsno
APIs and other access methodsJava Client API
Memcached protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
C++ API
Java API
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
All JVM based languages
C++
Groovy
Java
Scala
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresin SQL-layer onlyuser defined functionsuser defined functionsnono
Triggersnoyes infoCache Event Listenersyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityin SQL-layer onlynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodenonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlnoAccess rights per client and object definableAccess rights for users and roles on table levelnono

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More resources
FoundationDBGeodeKineticaSpark SQLTerarkDB
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