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DBMS > Databricks vs. mSQL vs. Postgres-XL vs. SAP SQL Anywhere vs. Spark SQL

System Properties Comparison Databricks vs. mSQL vs. Postgres-XL vs. SAP SQL Anywhere vs. Spark SQL

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparisonSpark 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.mSQL (Mini SQL) is a simple and lightweight RDBMSBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environmentsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSRelational 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
Score1.27
Rank#169  Overall
#76  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score3.95
Rank#80  Overall
#42  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.databricks.comhughestech.com.au/­products/­msqlwww.postgres-xl.orgwww.sap.com/­products/­technology-platform/­sql-anywhere.htmlspark.apache.org/­sql
Technical documentationdocs.databricks.comwww.postgres-xl.org/­documentationhelp.sap.com/­docs/­SAP_SQL_Anywherespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksHughes TechnologiesSAP infoformerly SybaseApache Software Foundation
Initial release201319942014 infosince 2012, originally named StormDB19922014
Current release4.4, October 202110 R1, October 201817, July 20153.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infofree licenses can be providedOpen Source infoMozilla public licensecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCCScala
Server operating systemshostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
macOS
AIX
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.yesnoyes infoXML type, but no XML query functionalityyesno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLwith Databricks SQLA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersyes infodistributed, parallel query executionyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
HTTP API
JDBC
ODBC
JDBC
ODBC
Supported programming languagesPython
R
Scala
C
C++
Delphi
Java
Perl
PHP
Tcl
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnouser defined functionsyes, in C/C++, Java, .Net or Perlno
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioningnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneSource-replica replication infoDatabase mirroringnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoMVCCACIDno
Concurrency infoSupport for concurrent manipulation of datayesnoyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno
More information provided by the system vendor
DatabricksmSQL infoMini SQLPostgres-XLSAP SQL Anywhere infoformerly called Adaptive Server AnywhereSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksmSQL infoMini SQLPostgres-XLSAP SQL Anywhere infoformerly called Adaptive Server AnywhereSpark SQL
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