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DBMS > Databricks vs. Kinetica vs. RisingWave

System Properties Comparison Databricks vs. Kinetica vs. RisingWave

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonKinetica  Xexclude from comparisonRisingWave  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.Fully vectorized database across both GPUs and CPUsA distributed RDBMS for stream processing, wire-compatible with PostgreSQL
Primary database modelDocument 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
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.64
Rank#238  Overall
#110  Relational DBMS
Websitewww.databricks.comwww.kinetica.comwww.risingwave.com/­database
Technical documentationdocs.databricks.comdocs.kinetica.comdocs.risingwave.com/­docs/­current/­intro
DeveloperDatabricksKineticaRisingWave Labs
Initial release201320122022
Current release7.1, August 20211.2, September 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 languageC, C++Rust
Server operating systemshostedLinuxDocker
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesStandard SQL-types and JSON
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 indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
PostgreSQL wire protocol
Supported programming languagesPython
R
Scala
C++
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsUDFs in Python or Java
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyes
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.noyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users and roles on table levelUsers and Roles
More information provided by the system vendor
DatabricksKineticaRisingWave
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksKineticaRisingWave
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