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DBMS > Databricks vs. Hive vs. Infobright vs. Spark SQL

System Properties Comparison Databricks vs. Hive vs. Infobright vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHive  Xexclude from comparisonInfobright  Xexclude from comparisonSpark SQL  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 HadoopHigh performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSRelational 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
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.96
Rank#194  Overall
#91  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.databricks.comhive.apache.orgignitetech.com/­softwarelibrary/­infobrightdbspark.apache.org/­sql
Technical documentationdocs.databricks.comcwiki.apache.org/­confluence/­display/­Hive/­Homespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksApache Software Foundation infoinitially developed by FacebookIgnite Technologies Inc.; formerly InfoBright Inc.Apache Software Foundation
Initial release2013201220052014
Current release3.1.3, April 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCScala
Server operating systemshostedAll OS with a Java VMLinux
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
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.yesnono
Secondary indexesyesyesno infoKnowledge Grid Technology used insteadno
SQL infoSupport of SQLwith Databricks SQLSQL-like DML and DDL statementsyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesPython
R
Scala
C++
Java
PHP
Python
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infouser defined functions and integration of map-reducenono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and rolesfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesno
More information provided by the system vendor
DatabricksHiveInfobrightSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksHiveInfobrightSpark SQL
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