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DBMS > Amazon Redshift vs. EJDB vs. FoundationDB vs. ObjectBox vs. Spark SQL

System Properties Comparison Amazon Redshift vs. EJDB vs. FoundationDB vs. ObjectBox vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonEJDB  Xexclude from comparisonFoundationDB  Xexclude from comparisonObjectBox  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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 toolsEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Ordered key-value store. Core features are complimented by layers.Extremely fast embedded database for small devices, IoT and MobileSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Object oriented DBMSRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score16.88
Rank#35  Overall
#22  Relational DBMS
Score0.31
Rank#296  Overall
#44  Document stores
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­redshiftgithub.com/­Softmotions/­ejdbgithub.com/­apple/­foundationdbobjectbox.iospark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­redshiftgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdapple.github.io/­foundationdbdocs.objectbox.iospark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazon (based on PostgreSQL)SoftmotionsFoundationDBObjectBox LimitedApache Software Foundation
Initial release20122012201320172014
Current release6.2.28, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPLv2Open Source infoApache 2.0Open Source infoApache License 2.0Open 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 languageCCC++C and C++Scala
Server operating systemshostedserver-lessLinux
OS X
Windows
Android
iOS
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyesschema-freeschema-free infosome layers support schemasyesyes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idno infosome layers support typingyesyes
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 indexesrestrictednonoyesno
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardnosupported in specific SQL layer onlynoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
in-process shared libraryProprietary native APIJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Pythonnoin SQL-layer onlynono
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyesonline/offline synchronization between client and servernone
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 systemno infotypically not needed, however similar functionality with collection joins possiblein SQL-layer onlyyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyesyes
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.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardnonoyesno
More information provided by the system vendor
Amazon RedshiftEJDBFoundationDBObjectBoxSpark SQL
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