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DBMS > Apache Impala vs. mSQL vs. OrigoDB vs. Spark SQL

System Properties Comparison Apache Impala vs. mSQL vs. OrigoDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopmSQL (Mini SQL) is a simple and lightweight RDBMSA fully ACID in-memory object graph databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSDocument store
Object oriented DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score1.67
Rank#151  Overall
#70  Relational DBMS
Score0.03
Rank#378  Overall
#51  Document stores
#18  Object oriented DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orghughestech.com.au/­products/­msqlorigodb.comspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmlorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHughes TechnologiesRobert Friberg et alApache Software Foundation
Initial release201319942009 infounder the name LiveDB2014
Current release4.1.0, June 20224.4, October 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree licenses can be providedOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CC#Scala
Server operating systemsLinuxAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesUser defined using .NET types and collectionsyes
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 infocan be achieved using .NETno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
.NET Client API
HTTP API
LINQ
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Delphi
Java
Perl
PHP
Tcl
.NetJava
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesno
Triggersnonoyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistencynone
Foreign keys infoReferential integritynonodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesnoyesyes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoRole based authorizationno

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More resources
Apache ImpalamSQL infoMini SQLOrigoDBSpark SQL
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