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DBMS > Databricks vs. Microsoft Azure SQL Database vs. Microsoft Azure Synapse Analytics vs. Sphinx vs. Splice Machine

System Properties Comparison Databricks vs. Microsoft Azure SQL Database vs. Microsoft Azure Synapse Analytics vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  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.Database as a Service offering with high compatibility to Microsoft SQL ServerElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSSearch engineRelational DBMS
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
Score76.78
Rank#16  Overall
#11  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.databricks.comazure.microsoft.com/­en-us/­products/­azure-sql/­databaseazure.microsoft.com/­services/­synapse-analyticssphinxsearch.comsplicemachine.com
Technical documentationdocs.databricks.comdocs.microsoft.com/­en-us/­azure/­azure-sqldocs.microsoft.com/­azure/­synapse-analyticssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperDatabricksMicrosoftMicrosoftSphinx Technologies Inc.Splice Machine
Initial release20132010201620012014
Current releaseV123.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C++Java
Server operating systemshostedhostedhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLwith Databricks SQLyesyesSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesPython
R
Scala
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
PHP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesTransact SQLTransact SQLnoyes infoJava
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, with always 3 replicas availableyesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyesnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
DatabricksMicrosoft Azure SQL Database infoformerly SQL AzureMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSphinxSplice Machine
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksMicrosoft Azure SQL Database infoformerly SQL AzureMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSphinxSplice Machine
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