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DBMS > Datomic vs. Sadas Engine vs. SiriDB vs. Spark SQL

System Properties Comparison Datomic vs. Sadas Engine vs. SiriDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonSadas Engine  Xexclude from comparisonSiriDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilitySADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsOpen Source Time Series DBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score0.07
Rank#378  Overall
#42  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.datomic.comwww.sadasengine.comsiridb.comspark.apache.org/­sql
Technical documentationdocs.datomic.comwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationdocs.siridb.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectSADAS s.r.l.CesbitApache Software Foundation
Initial release2012200620172014
Current release1.0.7075, December 20238.03.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infofree trial version availableOpen Source infoMIT LicenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC++CScala
Server operating systemsAll OS with a Java VMAIX
Linux
Windows
LinuxLinux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infoNumeric datayes
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoyesnoSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Proprietary protocol
HTTP APIJDBC
ODBC
Supported programming languagesClojure
Java
.Net
C
C#
C++
Groovy
Java
PHP
Python
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsnonono
TriggersBy using transaction functionsnonono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peershorizontal partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersnoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 developmentyes infomanaged by 'Learn by Usage'yesno
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardsimple rights management via user accountsno

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More resources
DatomicSadas EngineSiriDBSpark SQL
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