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DBMS > Hive vs. Spark SQL vs. StarRocks vs. SWC-DB

System Properties Comparison Hive vs. Spark SQL vs. StarRocks vs. SWC-DB

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonSpark SQL  Xexclude from comparisonStarRocks  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopSpark SQL is a component on top of 'Spark Core' for structured data processingAn open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics infoForked from Apache DorisA high performance, scalable Wide Column DBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMSWide column store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.93
Rank#198  Overall
#93  Relational DBMS
Score0.08
Rank#364  Overall
#13  Wide column stores
Websitehive.apache.orgspark.apache.org/­sqlwww.starrocks.iogithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homespark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.starrocks.io/­en-us/­latest/­introduction/­StarRocks_intro
DeveloperApache Software Foundation infoinitially developed by FacebookApache Software FoundationThe Linux Foundation infosince Feb 2023Alex Kashirin
Initial release2012201420202020
Current release3.1.3, April 20223.5.0 ( 2.13), September 20232.5.3, March 20230.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC++, JavaC++
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
LinuxLinux
Data schemeyesyesyesschema-free
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 indexesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsyesSQL-like query language
APIs and other access methodsJDBC
ODBC
Thrift
JDBC
ODBC
JDBC
MySQL protocol
Proprietary protocol
Thrift
Supported programming languagesC++
Java
PHP
Python
Java
Python
R
Scala
JavaC++
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenouser defined functionsno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corehorizontal partitioning (by range and hash)Sharding
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 MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
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 rolesnoRole based access control and fine grained access rights

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More resources
HiveSpark SQLStarRocksSWC-DB infoSuper Wide Column Database
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