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DBMS > Databricks vs. GridGain vs. StarRocks

System Properties Comparison Databricks vs. GridGain vs. StarRocks

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGridGain  Xexclude from comparisonStarRocks  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.GridGain is an in-memory computing platform, built on Apache IgniteAn open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics infoForked from Apache Doris
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Relational 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
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score1.04
Rank#189  Overall
#88  Relational DBMS
Websitewww.databricks.comwww.gridgain.comwww.starrocks.io
Technical documentationdocs.databricks.comwww.gridgain.com/­docs/­index.htmldocs.starrocks.io/­en-us/­latest/­introduction/­StarRocks_intro
DeveloperDatabricksGridGain Systems, Inc.The Linux Foundation infosince Feb 2023
Initial release201320072020
Current releaseGridGain 8.5.12.5.3, March 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC++, Java
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
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.yesyesno
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
MySQL protocol
Supported programming languagesPython
R
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)user defined functions
Triggersyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range and hash)
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
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 controlSecurity Hooks for custom implementationsRole based access control and fine grained access rights
More information provided by the system vendor
DatabricksGridGainStarRocks
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksGridGainStarRocks
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