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DBMS > FoundationDB vs. GridGain vs. Hive vs. Spark SQL

System Properties Comparison FoundationDB vs. GridGain vs. Hive vs. Spark SQL

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Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonGridGain  Xexclude from comparisonHive  Xexclude from comparisonSpark SQL  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.GridGain is an in-memory computing platform, built on Apache Ignitedata warehouse software for querying and managing large distributed datasets, built on HadoopSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Key-value store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­apple/­foundationdbwww.gridgain.comhive.apache.orgspark.apache.org/­sql
Technical documentationapple.github.io/­foundationdbwww.gridgain.com/­docs/­index.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFoundationDBGridGain Systems, Inc.Apache Software Foundation infoinitially developed by FacebookApache Software Foundation
Initial release2013200720122014
Current release6.2.28, November 2020GridGain 8.5.13.1.3, April 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, C++, .NetJavaScala
Server operating systemsLinux
OS X
Windows
Linux
OS X
Solaris
Windows
All OS with a Java VMLinux
OS X
Windows
Data schemeschema-free infosome layers support schemasyesyesyes
Typing infopredefined data types such as float or dateno infosome layers support typingyesyesyes
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
Secondary indexesnoyesyesno
SQL infoSupport of SQLsupported in specific SQL layer onlyANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Thrift
JDBC
ODBC
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresin SQL-layer onlyyes (compute grid and cache interceptors can be used instead)yes infouser defined functions and integration of map-reduceno
Triggersnoyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)yes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityin SQL-layer onlynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
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.yesno
User concepts infoAccess controlnoSecurity Hooks for custom implementationsAccess rights for users, groups and rolesno

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More resources
FoundationDBGridGainHiveSpark SQL
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