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DBMS > Datastax Enterprise vs. Hive vs. Spark SQL

System Properties Comparison Datastax Enterprise vs. Hive vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatastax Enterprise  Xexclude from comparisonHive  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.data warehouse software for querying and managing large distributed datasets, built on HadoopSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelWide column storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.63
Rank#53  Overall
#4  Wide column stores
Score77.89
Rank#17  Overall
#11  Relational DBMS
Score20.62
Rank#36  Overall
#22  Relational DBMS
Websitewww.datastax.com/­products/­datastax-enterprisehive.apache.orgspark.apache.org/­sql
Technical documentationdocs.datastax.comcwiki.apache.org/­confluence/­display/­Hive/­Homespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDataStaxApache Software Foundation infoinitially developed by FacebookApache Software Foundation
Initial release201120122014
Current release6.8, April 20203.1.3, April 20223.3.0 ( 2.13), June 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageJavaJavaScala
Server operating systemsLinux
OS X
All OS with a Java VMLinux
OS X
Windows
Data schemeschema-freeyesyes
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.nono
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statements (CQL); Spark SQLSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
JDBC
ODBC
Thrift
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceno
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"Shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter aware, advanced replication for edge computingselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsnono
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.yesno
User concepts infoAccess controlAccess rights for users can be defined per objectAccess rights for users, groups and rolesno
More information provided by the system vendor
Datastax EnterpriseHiveSpark SQL
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
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Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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Datastax EnterpriseHiveSpark SQL
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