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DBMS > Amazon Redshift vs. FoundationDB vs. Microsoft Access vs. SiteWhere vs. Spark SQL

System Properties Comparison Amazon Redshift vs. FoundationDB vs. Microsoft Access vs. SiteWhere vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonFoundationDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSiteWhere  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.
DescriptionLarge scale data warehouse service for use with business intelligence toolsOrdered key-value store. Core features are complimented by layers.Microsoft 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.)M2M integration platform for persisting/querying time series dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score16.88
Rank#35  Overall
#22  Relational DBMS
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­redshiftgithub.com/­apple/­foundationdbwww.microsoft.com/­en-us/­microsoft-365/­accessgithub.com/­sitewhere/­sitewherespark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­redshiftapple.github.io/­foundationdbdeveloper.microsoft.com/­en-us/­accesssitewhere1.sitewhere.io/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazon (based on PostgreSQL)FoundationDBMicrosoftSiteWhereApache Software Foundation
Initial release20122013199220102014
Current release6.2.28, November 20201902 (16.0.11328.20222), March 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infoBundled with Microsoft OfficeOpen Source infoCommon Public Attribution License Version 1.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++C++JavaScala
Server operating systemshostedLinux
OS X
Windows
Windows infoNot a real database server, but making use of DLLsLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesschema-free infosome layers support schemasyespredefined schemeyes
Typing infopredefined data types such as float or dateyesno 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.nonono
Secondary indexesrestrictednoyesnono
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardsupported in specific SQL layer onlyyes infobut not compliant to any SQL standardnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
ADO.NET
DAO
ODBC
OLE DB
HTTP RESTJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Pythonin SQL-layer onlyyes infosince Access 2010 using the ACE-engineno
Triggersnonoyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infobased on HBaseyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesnoneselectable replication factor infobased on HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyLinearizable consistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemin SQL-layer onlyyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infobut no files for transaction loggingnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardnono infoa simple user-level security was built in till version Access 2003Users with fine-grained authorization conceptno

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More resources
Amazon RedshiftFoundationDBMicrosoft AccessSiteWhereSpark SQL
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