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DBMS > Databricks vs. LeanXcale vs. Microsoft SQL Server vs. mSQL

System Properties Comparison Databricks vs. LeanXcale vs. Microsoft SQL Server vs. mSQL

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonmSQL infoMini SQL  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 highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesMicrosofts flagship relational DBMSmSQL (Mini SQL) is a simple and lightweight RDBMS
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score60.74
Rank#19  Overall
#3  Document stores
#13  Relational DBMS
Score0.22
Rank#318  Overall
#44  Key-value stores
#142  Relational DBMS
Score924.35
Rank#3  Overall
#3  Relational DBMS
Score1.50
Rank#158  Overall
#75  Relational DBMS
Websitedatabricks.comwww.leanxcale.comwww.microsoft.com/­en-us/­sql-serverhughestech.com.au/­products/­msql
Technical documentationdatabricks.com/­documentationdocs.microsoft.com/­en-US/­sql/­sql-server
DeveloperDatabricksLeanXcaleMicrosoftHughes Technologies
Initial release2013201519891994
Current releaseSQL Server 2019, November 20194.4, October 2021
License infoCommercial or Open SourceOpen Sourcecommercialcommercial inforestricted free version is availablecommercial infofree licenses can be provided
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C
Server operating systemshostedLinux
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
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.yesyesno
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyes infothrough Apache DerbyyesA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggers
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
JDBC
ODBC
Supported programming languagesPython
R
Scala
C
Java
Scala
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
C
C++
Delphi
Java
Perl
PHP
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javano
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodestables can be distributed across several files (horizontal partitioning); sharding through federationnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, but depending on the SQL-Server Editionnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistencynone
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesno
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardno
More information provided by the system vendor
DatabricksLeanXcaleMicrosoft SQL ServermSQL infoMini SQL
Specific characteristicsFull ACID and full SQL operational database with analytical queries over operational...
» more
Competitive advantagesLinear scalability upto 100s of nodes (tested with 100 nodes and TPC-C).
» more
Typical application scenariosHybrid Transactional-Analytical Processing (HTAP) requiring an operational database...
» more
Key customersbanking/finance/fintech, telco, insurance, traveltech, M2M/IoT, retail
» more
Market metrics15 beta testers
» more
Licensing and pricing modelsannual fee covering license and support based on number of physical cores
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
DatabricksLeanXcaleMicrosoft SQL ServermSQL infoMini SQL
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