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DBMS > Apache Impala vs. Quasardb vs. RethinkDB vs. Spark SQL

System Properties Comparison Apache Impala vs. Quasardb vs. RethinkDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonQuasardb  Xexclude from comparisonRethinkDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDistributed, high-performance timeseries databaseDBMS for the Web with a mechanism to push updated query results to applications in realtime.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSDocument storeRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score2.74
Rank#105  Overall
#19  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgquasar.airethinkdb.comspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmldoc.quasar.ai/­masterrethinkdb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaquasardbThe Linux Foundation infosince July 2017Apache Software Foundation
Initial release2013200920092014
Current release4.1.0, June 20223.14.1, January 20242.4.1, August 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache Version 2Open 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++C++C++Scala
Server operating systemsLinuxBSD
Linux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infointeger and binaryyes infostring, binary, float, bool, date, geometryyes
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.nononono
Secondary indexesyesyes infowith tagsyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languagenoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
HTTP APIJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenono
TriggersnonoClient-side triggers through changefeedsno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoconsistent hashingSharding inforange basedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication with selectable replication factorSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducewith Hadoop integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-document operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCC basedyes
Durability infoSupport for making data persistentyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modenono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosCryptographically strong user authentication and audit trailyes infousers and table-level permissionsno

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More resources
Apache ImpalaQuasardbRethinkDBSpark SQL
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