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DBMS > Impala vs. Spark SQL

System Properties Comparison Impala vs. Spark SQL

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Our visitors often compare Impala and Spark SQL with Hive, HBase and Oracle.

Editorial information provided by DB-Engines
NameImpala  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.86
Rank#37  Overall
#23  Relational DBMS
Score16.76
Rank#35  Overall
#21  Relational DBMS
Websitewww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.htmlspark.apache.org/­sql
Technical documentationwww.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperClouderaApache Software Foundation
Initial release20132014
Current release3.2.0, March 2019v2.4.3, May 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Scala
Server operating systemsLinuxLinux
OS X
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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.nono
Secondary indexesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCJava
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno

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More resources
ImpalaSpark SQL
Conferences and events

Spark Summit Europe 2019
Amsterdam, Netherlands, 15-17 October 2019

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