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DBMS > Amazon Redshift vs. Hive vs. ObjectBox vs. Spark SQL

System Properties Comparison Amazon Redshift vs. Hive vs. ObjectBox vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonHive  Xexclude from comparisonObjectBox  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsdata warehouse software for querying and managing large distributed datasets, built on HadoopExtremely 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 DBMSRelational DBMSObject oriented DBMSRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.94
Rank#34  Overall
#21  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­redshifthive.apache.orgobjectbox.iospark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­redshiftcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.objectbox.iospark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazon (based on PostgreSQL)Apache Software Foundation infoinitially developed by FacebookObjectBox LimitedApache Software Foundation
Initial release2012201220172014
Current release3.1.3, April 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache License 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaC and C++Scala
Server operating systemshostedAll OS with a Java VMAndroid
iOS
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesrestrictedyesyesno
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardSQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Thrift
Proprietary native APIJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
PHP
Python
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 Pythonyes infouser defined functions and integration of map-reducenono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factoronline/offline synchronization between client and servernone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
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.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and rolesyesno
More information provided by the system vendor
Amazon RedshiftHiveObjectBoxSpark SQL
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