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DBMS > Databricks vs. OpenQM vs. Vitess

System Properties Comparison Databricks vs. OpenQM vs. Vitess

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonOpenQM infoalso called QM  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.QpenQM is a high-performance, self-tuning, multi-value DBMSScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument store
Relational DBMS
Multivalue DBMSRelational DBMS
Secondary database modelsDocument 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
Score0.34
Rank#284  Overall
#10  Multivalue DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitewww.databricks.comwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qmvitess.io
Technical documentationdocs.databricks.comvitess.io/­docs
DeveloperDatabricksRocket Software, originally Martin PhillipsThe Linux Foundation, PlanetScale
Initial release201319932013
Current release3.4-1215.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoGPLv2, extended commercial license availableOpen 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 languageGo
Server operating systemshostedAIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Docker
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yes infowith some exceptionsyes
Typing infopredefined data types such as float or dateyes
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.yesyes
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLnoyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesPython
R
Scala
.Net
Basic
C
Java
Objective C
PHP
Python
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 aggregatesyesyes infoproprietary syntax
Triggersyesyes
Partitioning methods infoMethods for storing different data on different nodesyesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
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 dataACIDACIDACID 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.noyes
User concepts infoAccess controlAccess rights can be defined down to the item levelUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
DatabricksOpenQM infoalso called QMVitess
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksOpenQM infoalso called QMVitess
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