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DBMS > Datomic vs. Microsoft Azure Synapse Analytics vs. Splice Machine vs. SQLite

System Properties Comparison Datomic vs. Microsoft Azure Synapse Analytics vs. Splice Machine vs. SQLite

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSplice Machine  Xexclude from comparisonSQLite  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkWidely used embeddable, in-process RDBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score114.32
Rank#10  Overall
#7  Relational DBMS
Websitewww.datomic.comazure.microsoft.com/­services/­synapse-analyticssplicemachine.comwww.sqlite.org
Technical documentationdocs.datomic.comdocs.microsoft.com/­azure/­synapse-analyticssplicemachine.com/­how-it-workswww.sqlite.org/­docs.html
DeveloperCognitectMicrosoftSplice MachineDwayne Richard Hipp
Initial release2012201620142000
Current release1.0.6735, June 20233.1, March 20213.45.3  (15 April 2024), April 2024
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoPublic Domain
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++JavaC
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Solaris
Windows
server-less
Data schemeyesyesyesyes infodynamic column types
Typing infopredefined data types such as float or dateyesyesyesyes infonot rigid because of 'dynamic typing' concept.
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.nonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoyesyesyes infoSQL-92 is not fully supported
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
ADO.NET infoinofficial driver
JDBC infoinofficial driver
ODBC infoinofficial driver
Supported programming languagesClojure
Java
C#
Java
PHP
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl
Server-side scripts infoStored proceduresyes infoTransaction FunctionsTransact SQLyes infoJavano
TriggersBy using transaction functionsnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding, horizontal partitioningShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes infovia file-system locks
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlnoyesAccess rights for users, groups and roles according to SQL-standardno

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More resources
DatomicMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSplice MachineSQLite
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