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DBMS > Apache Impala vs. HBase vs. Spark SQL

System Properties Comparison Apache Impala vs. HBase vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHBase  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopWide-column store based on Apache Hadoop and on concepts of BigTableSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSWide column storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orghbase.apache.orgspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmlhbase.apache.org/­book.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation
Initial release201320082014
Current release4.1.0, June 20222.3.4, January 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaScala
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Data schemeyesschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyes
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 indexesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoCoprocessors in Javano
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)no
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACno

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More resources
Apache ImpalaHBaseSpark SQL
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