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DBMS > Databricks vs. HBase vs. MySQL vs. Rockset

System Properties Comparison Databricks vs. HBase vs. MySQL vs. Rockset

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHBase  Xexclude from comparisonMySQL  Xexclude from comparisonRockset  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.Wide-column store based on Apache Hadoop and on concepts of BigTableWidely used open source RDBMSA scalable, reliable search and analytics service in the cloud, built on RocksDB
Primary database modelDocument store
Relational DBMS
Wide column storeRelational DBMS infoKey/Value like access via memcached APIDocument store
Secondary database modelsDocument store
Spatial DBMS
Relational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score1083.74
Rank#2  Overall
#2  Relational DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Websitewww.databricks.comhbase.apache.orgwww.mysql.comrockset.com
Technical documentationdocs.databricks.comhbase.apache.org/­book.htmldev.mysql.com/­docdocs.rockset.com
DeveloperDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetOracle infosince 2010, originally MySQL AB, then SunRockset
Initial release2013200819952019
Current release2.3.4, January 20218.4.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoGPL version 2. Commercial licenses with extended functionallity are availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.
Implementation languageJavaC and C++C++
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
FreeBSD
Linux
OS X
Solaris
Windows
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleyesschema-free
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyesdynamic typing
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.yesnoyesno infoingestion from XML files supported
Secondary indexesyesnoyesall fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLnoyes infowith proprietary extensionsRead-only SQL queries, including JOINs
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
ADO.NET
JDBC
ODBC
Proprietary native API
HTTP REST
Supported programming languagesPython
R
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoCoprocessors in Javayes infoproprietary syntaxno
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning, sharding with MySQL Cluster or MySQL FabricAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)ACID infonot for MyISAM storage engineno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
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.noyesyes
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACUsers with fine-grained authorization concept infono user groups or rolesAccess rights for users and organizations can be defined via Rockset console
More information provided by the system vendor
DatabricksHBaseMySQLRockset
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
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