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DBMS > Apache Hive vs. Databricks vs. Datastax Enterprise

System Properties Comparison Apache Hive vs. Databricks vs. Datastax Enterprise

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Editorial information provided by DB-Engines
NameApache Hive  Xexclude from comparisonDatabricks  Xexclude from comparisonDatastax Enterprise  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.DataStax 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.
Primary database modelRelational DBMSDocument store
Relational DBMS
Wide column store
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score53.09
Rank#18  Overall
#12  Relational DBMS
Score87.68
Rank#13  Overall
#2  Document stores
#9  Relational DBMS
Score4.74
Rank#64  Overall
#4  Wide column stores
Websitehive.apache.orgwww.databricks.comwww.datastax.com/­products/­datastax-enterprise
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.databricks.comdocs.datastax.com
DeveloperApache Software Foundation infoinitially developed by FacebookDatabricksDataStax
Initial release201220132011
Current release3.1.3, April 20226.8, April 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesyes
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.yesno
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLSQL-like DML and DDL statements (CQL); Spark SQL
APIs and other access methodsJDBC
ODBC
Thrift
JDBC
ODBC
RESTful HTTP API
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
Supported programming languagesC++
Java
PHP
Python
Python
R
Scala
C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesno
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesconfigurable replication factor, datacenter aware, advanced replication for edge computing
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno infoAtomicity and isolation are supported for single operations
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.noyes
User concepts infoAccess controlAccess rights for users, groups and rolesAccess rights for users can be defined per object
More information provided by the system vendor
Apache HiveDatabricksDatastax Enterprise
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
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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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Apache HiveDatabricksDatastax Enterprise
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