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DBMS > Databricks vs. HEAVY.AI vs. Oracle Rdb

System Properties Comparison Databricks vs. HEAVY.AI vs. Oracle Rdb

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonOracle Rdb  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.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score2.10
Rank#126  Overall
#61  Relational DBMS
Score1.08
Rank#187  Overall
#85  Relational DBMS
Websitewww.databricks.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.oracle.com/­database/­technologies/­related/­rdb.html
Technical documentationdocs.databricks.comdocs.heavy.aiwww.oracle.com/­database/­technologies/­related/­rdb-doc.html
DeveloperDatabricksHEAVY.AI, Inc.Oracle, originally developed by Digital Equipment Corporation (DEC)
Initial release201320161984
Current release5.10, January 20227.4.1.1, 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDA
Server operating systemshostedLinuxHP Open VMS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesFlexible Schema (defined schema, partial schema, 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.yesnono
Secondary indexesyesnoyes
SQL infoSupport of SQLwith Databricks SQLyesyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
Supported programming languagesPython
R
Scala
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesno
Triggersno
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyes, on a single node
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.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Oracle Rdb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Oracle Rdb
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