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DBMS > Databricks vs. Greenplum vs. Hive

System Properties Comparison Databricks vs. Greenplum vs. Hive

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGreenplum  Xexclude from comparisonHive  Xexclude from comparison
DescriptionThe 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.Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.data warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Websitewww.databricks.comgreenplum.orghive.apache.org
Technical documentationdocs.databricks.comdocs.greenplum.orgcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperDatabricksPivotal Software Inc.Apache Software Foundation infoinitially developed by Facebook
Initial release201320052012
Current release7.0.0, September 20233.1.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemshostedLinuxAll OS with a Java VM
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
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.yesyes infosince Version 4.2
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
ODBC
Thrift
Supported programming languagesPython
R
Scala
C
Java
Perl
Python
R
C++
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesyes infouser defined functions and integration of map-reduce
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
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.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles
More information provided by the system vendor
DatabricksGreenplumHive
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksGreenplumHive
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