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DBMS > FoundationDB vs. Hive vs. Microsoft Access vs. Spark SQL

System Properties Comparison FoundationDB vs. Hive vs. Microsoft Access vs. Spark SQL

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Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Access  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.data warehouse software for querying and managing large distributed datasets, built on HadoopMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Spark 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
Relational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.07
Rank#188  Overall
#31  Document stores
#28  Key-value stores
#86  Relational DBMS
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score105.40
Rank#11  Overall
#8  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­apple/­foundationdbhive.apache.orgwww.microsoft.com/­en-us/­microsoft-365/­accessspark.apache.org/­sql
Technical documentationapple.github.io/­foundationdbcwiki.apache.org/­confluence/­display/­Hive/­Homedeveloper.microsoft.com/­en-us/­accessspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFoundationDBApache Software Foundation infoinitially developed by FacebookMicrosoftApache Software Foundation
Initial release2013201219922014
Current release6.2.28, November 20203.1.3, April 20221902 (16.0.11328.20222), March 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2commercial infoBundled with Microsoft OfficeOpen 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++JavaC++Scala
Server operating systemsLinux
OS X
Windows
All OS with a Java VMWindows infoNot a real database server, but making use of DLLsLinux
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.no
Secondary indexesnoyesyesno
SQL infoSupport of SQLsupported in specific SQL layer onlySQL-like DML and DDL statementsyes infobut not compliant to any SQL standardSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Thrift
ADO.NET
DAO
ODBC
OLE DB
JDBC
ODBC
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C++
Java
PHP
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Java
Python
R
Scala
Server-side scripts infoStored proceduresin SQL-layer onlyyes infouser defined functions and integration of map-reduceyes infosince Access 2010 using the ACE-engineno
Triggersnonoyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyEventual Consistency
Foreign keys infoReferential integrityin SQL-layer onlynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infobut no files for transaction loggingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlnoAccess rights for users, groups and rolesno infoa simple user-level security was built in till version Access 2003no

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More resources
FoundationDBHiveMicrosoft AccessSpark SQL
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