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DBMS > Databricks vs. Drizzle vs. GridGain vs. Kinetica vs. Oracle Rdb

System Properties Comparison Databricks vs. Drizzle vs. GridGain vs. Kinetica vs. Oracle Rdb

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonGridGain  Xexclude from comparisonKinetica  Xexclude from comparisonOracle Rdb  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
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.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.GridGain is an in-memory computing platform, built on Apache IgniteFully vectorized database across both GPUs and CPUs
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series 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
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score1.14
Rank#178  Overall
#80  Relational DBMS
Websitewww.databricks.comwww.gridgain.comwww.kinetica.comwww.oracle.com/­database/­technologies/­related/­rdb.html
Technical documentationdocs.databricks.comwww.gridgain.com/­docs/­index.htmldocs.kinetica.comwww.oracle.com/­database/­technologies/­related/­rdb-doc.html
DeveloperDatabricksDrizzle project, originally started by Brian AkerGridGain Systems, Inc.KineticaOracle, originally developed by Digital Equipment Corporation (DEC)
Initial release20132008200720121984
Current release7.2.4, September 2012GridGain 8.5.17.1, August 20217.4.1.1, 2021
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java, C++, .NetC, C++
Server operating systemshostedFreeBSD
Linux
OS X
Linux
OS X
Solaris
Windows
LinuxHP Open VMS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyesyesyes
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.yesyesnono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyes infowith proprietary extensionsANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
RESTful HTTP API
Supported programming languagesPython
R
Scala
C
C++
Java
PHP
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes (compute grid and cache interceptors can be used instead)user defined functions
Triggersno infohooks for callbacks inside the server can be used.yes (cache interceptors and events)yes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
yes (replicated cache)Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnoyes, on a single node
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPSecurity Hooks for custom implementationsAccess rights for users and roles on table level
More information provided by the system vendor
DatabricksDrizzleGridGainKineticaOracle Rdb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksDrizzleGridGainKineticaOracle Rdb
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