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DBMS > Databricks vs. Hive vs. MonetDB vs. Riak KV

System Properties Comparison Databricks vs. Hive vs. MonetDB vs. Riak KV

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHive  Xexclude from comparisonMonetDB  Xexclude from comparisonRiak KV  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.data warehouse software for querying and managing large distributed datasets, built on HadoopA relational database management system that stores data in columnsDistributed, fault tolerant key-value store
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Websitewww.databricks.comhive.apache.orgwww.monetdb.org
Technical documentationdocs.databricks.comcwiki.apache.org/­confluence/­display/­Hive/­Homewww.monetdb.org/­Documentationwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperDatabricksApache Software Foundation infoinitially developed by FacebookMonetDB BVOpenSource, formerly Basho Technologies
Initial release2013201220042009
Current release3.1.3, April 2022Dec2023 (11.49), December 20233.2.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoMozilla Public License 2.0Open Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCErlang
Server operating systemshostedAll OS with a Java VMFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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 indexesyesyesyesrestricted
SQL infoSupport of SQLwith Databricks SQLSQL-like DML and DDL statementsyes infoSQL 2003 with some extensionsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
HTTP API
Native Erlang Interface
Supported programming languagesPython
R
Scala
C++
Java
PHP
Python
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infouser defined functions and integration of map-reduceyes, in SQL, C, RErlang
Triggersnoyesyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingSharding via remote tablesSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factornone infoSource-replica replication available in experimental statusselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
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.no
User concepts infoAccess controlAccess rights for users, groups and rolesfine grained access rights according to SQL-standardyes, using Riak Security
More information provided by the system vendor
DatabricksHiveMonetDBRiak KV
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHiveMonetDBRiak KV
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