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DBMS > Databricks vs. Microsoft SQL Server vs. Splice Machine vs. Typesense

System Properties Comparison Databricks vs. Microsoft SQL Server vs. Splice Machine vs. Typesense

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonSplice Machine  Xexclude from comparisonTypesense  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.Microsofts flagship relational DBMSOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSSearch engine
Secondary database modelsDocument store
Graph DBMS
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
Score821.56
Rank#3  Overall
#3  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.76
Rank#219  Overall
#14  Search engines
Websitewww.databricks.comwww.microsoft.com/­en-us/­sql-serversplicemachine.comtypesense.org
Technical documentationdocs.databricks.comlearn.microsoft.com/­en-US/­sql/­sql-serversplicemachine.com/­how-it-workstypesense.org/­docs
DeveloperDatabricksMicrosoftSplice Machine
Initial release2013198920142015
Current releaseSQL Server 2022, November 20223.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availableOpen Source infoAGPL 3.0, commercial license availableOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++
Server operating systemshostedLinux
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-free infopre-defined schema optional
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyesyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
JDBC
Native Spark Datasource
ODBC
RESTful HTTP API
Supported programming languagesPython
R
Scala
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresuser defined functions and aggregatesTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javayes infoJavano
Triggersyesyes
Partitioning methods infoMethods for storing different data on different nodestables can be distributed across several files (horizontal partitioning); sharding through federationShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, but depending on the SQL-Server EditionMulti-source replication
Source-replica replication
Multi-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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.noyesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
DatabricksMicrosoft SQL ServerSplice MachineTypesense
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksMicrosoft SQL ServerSplice MachineTypesense
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