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DBMS > Hive vs. Microsoft Azure Table Storage vs. Quasardb vs. Sequoiadb vs. Spark SQL

System Properties Comparison Hive vs. Microsoft Azure Table Storage vs. Quasardb vs. Sequoiadb vs. Spark SQL

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonQuasardb  Xexclude from comparisonSequoiadb  Xexclude from comparisonSpark SQL  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopA Wide Column Store for rapid development using massive semi-structured datasetsDistributed, high-performance timeseries databaseNewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSWide column storeTime Series DBMSDocument store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitehive.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tablesquasar.aiwww.sequoiadb.comspark.apache.org/­sql
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedoc.quasar.ai/­masterwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoinitially developed by FacebookMicrosoftquasardbSequoiadb Ltd.Apache Software Foundation
Initial release20122012200920132014
Current release3.1.3, April 20223.14.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++Scala
Server operating systemsAll OS with a Java VMhostedBSD
Linux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeyesschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infointeger and binaryyes infooid, date, timestamp, binary, regexyes
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 indexesyesnoyes infowith tagsyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query languageSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Thrift
RESTful HTTP APIHTTP APIproprietary protocol using JSONJDBC
ODBC
Supported programming languagesC++
Java
PHP
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoJavaScriptno
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infoconsistent hashingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with selectable replication factorSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingACIDDocument is locked during a transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes 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 rolesAccess rights based on private key authentication or shared access signaturesCryptographically strong user authentication and audit trailsimple password-based access controlno

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More resources
HiveMicrosoft Azure Table StorageQuasardbSequoiadbSpark SQL
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