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DBMS > Databricks vs. InterSystems IRIS vs. RisingWave

System Properties Comparison Databricks vs. InterSystems IRIS vs. RisingWave

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonInterSystems IRIS  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.A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilityA distributed RDBMS for stream processing, wire-compatible with PostgreSQL
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score99.29
Rank#12  Overall
#2  Document stores
#8  Relational DBMS
Score2.20
Rank#110  Overall
#20  Document stores
#17  Key-value stores
#1  Object oriented DBMS
#54  Relational DBMS
Score0.72
Rank#215  Overall
#101  Relational DBMS
Websitewww.databricks.comwww.intersystems.com/­products/­intersystems-iriswww.risingwave.com/­database
Technical documentationdocs.databricks.comdocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clsdocs.risingwave.com/­docs/­current/­intro
DeveloperDatabricksInterSystemsRisingWave Labs
Initial release201320182022
Current release2023.3, June 20231.2, 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRust
Server operating systemshostedAIX
Linux
macOS
Ubuntu
Windows
Docker
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)depending on used data modelyes
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.yesyesno
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyesyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
PostgreSQL wire protocol
Supported programming languagesPython
R
Scala
.Net
C++
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesUDFs in Python or Java
Triggersyesno
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
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
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.noyesyes
User concepts infoAccess controlyesUsers and Roles

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More resources
DatabricksInterSystems IRISRisingWave
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