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DBMS > Databricks vs. StarRocks vs. WakandaDB

System Properties Comparison Databricks vs. StarRocks vs. WakandaDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonStarRocks  Xexclude from comparisonWakandaDB  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.An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics infoForked from Apache DorisWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument store
Relational DBMS
Relational DBMSObject oriented 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
Score1.04
Rank#189  Overall
#88  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitewww.databricks.comwww.starrocks.iowakanda.github.io
Technical documentationdocs.databricks.comdocs.starrocks.io/­en-us/­latest/­introduction/­StarRocks_introwakanda.github.io/­doc
DeveloperDatabricksThe Linux Foundation infosince Feb 2023Wakanda SAS
Initial release201320202012
Current release2.5.3, March 20232.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaC++, JavaScript
Server operating systemshostedLinuxLinux
OS X
Windows
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.yesnono
Secondary indexesyesyes
SQL infoSupport of SQLwith Databricks SQLyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
MySQL protocol
RESTful HTTP API
Supported programming languagesPython
R
Scala
JavaJavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsyes
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by range and hash)none
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone
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 integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
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.nonono
User concepts infoAccess controlRole based access control and fine grained access rightsyes
More information provided by the system vendor
DatabricksStarRocksWakandaDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksStarRocksWakandaDB
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