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DBMS > Apache Impala vs. DataFS vs. Spark SQL

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDataFS  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSObject oriented DBMSRelational DBMS
Secondary database modelsDocument storeGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgnewdatabase.comspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmldev.mobiland.com/­Overview.xspspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMobiland AGApache Software Foundation
Initial release201320182014
Current release4.1.0, June 20221.1.263, October 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen 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++Scala
Server operating systemsLinuxWindowsLinux
OS X
Windows
Data schemeyesClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)yes
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 indexesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
.NET Client API
Proprietary client DLL
WinRT client
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C#
C++
VB.Net
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceno
Triggersnono, except callback-events from server when changes happenedno
Partitioning methods infoMethods for storing different data on different nodesShardingProprietary Sharding systemyes, 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 MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosWindows-Profileno

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More resources
Apache ImpalaDataFSSpark SQL
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