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DBMS > Amazon Redshift vs. Impala vs. Spark SQL

System Properties Comparison Amazon Redshift vs. Impala vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonImpala  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsAnalytic DBMS for HadoopSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score22.16
Rank#32  Overall
#19  Relational DBMS
Score16.94
Rank#37  Overall
#23  Relational DBMS
Score19.46
Rank#34  Overall
#21  Relational DBMS
Websiteaws.amazon.com/­redshiftwww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.htmlspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­redshiftdocs.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazon (based on PostgreSQL)ClouderaApache Software Foundation
Initial release201220132014
Current release3.4.0, April 20203.1.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++Scala
Server operating systemshostedLinuxLinux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesrestrictedyesno
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBCJava
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Pythonyes infouser defined functions and integration of map-reduceno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
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 roles infobased on Apache Sentry and Kerberosno

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More resources
Amazon RedshiftImpalaSpark SQL
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