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DBMS > Databricks vs. OpenMLDB vs. Vitess

System Properties Comparison Databricks vs. OpenMLDB vs. Vitess

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonOpenMLDB  Xexclude from comparisonVitess  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 machine learning database that provides a feature platform for training and inferenceScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument store
Relational DBMS
Time Series DBMSRelational DBMS
Secondary database modelsRelational DBMSDocument store
Spatial 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
Score0.10
Rank#359  Overall
#36  Time Series DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitewww.databricks.comopenmldb.aivitess.io
Technical documentationdocs.databricks.comopenmldb.ai/­docs/­zh/­mainvitess.io/­docs
DeveloperDatabricks4 Paradigm Inc.The Linux Foundation, PlanetScale
Initial release201320202013
Current release2024-2 February 202415.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, ScalaGo
Server operating systemshostedLinuxDocker
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)Fixed schemayes
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.yesno
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyesyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
SQLAlchemy
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesPython
R
Scala
C++
Go
Java
Python
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes infoproprietary syntax
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engine
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 controlfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
DatabricksOpenMLDBVitess
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksOpenMLDBVitess
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