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DBMS > Datomic vs. Firebase Realtime Database vs. Microsoft Azure Synapse Analytics vs. Splice Machine vs. SQream DB

System Properties Comparison Datomic vs. Firebase Realtime Database vs. Microsoft Azure Synapse Analytics vs. Splice Machine vs. SQream DB

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSplice Machine  Xexclude from comparisonSQream DB  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Elastic, 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 Sparka GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.74
Rank#224  Overall
#103  Relational DBMS
Websitewww.datomic.comfirebase.google.com/­products/­realtime-databaseazure.microsoft.com/­services/­synapse-analyticssplicemachine.comsqream.com
Technical documentationdocs.datomic.comfirebase.google.com/­docs/­databasedocs.microsoft.com/­azure/­synapse-analyticssplicemachine.com/­how-it-worksdocs.sqream.com
DeveloperCognitectGoogle infoacquired by Google 2014MicrosoftSplice MachineSQream Technologies
Initial release20122012201620142017
Current release1.0.7075, December 20233.1, March 20212022.1.6, December 2022
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC++JavaC++, CUDA, Haskell, Java, Scala
Server operating systemsAll OS with a Java VMhostedhostedLinux
OS X
Solaris
Windows
Linux
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes, ANSI Standard SQL Types
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 indexesyesyesyesyesno
SQL infoSupport of SQLnonoyesyesyes
APIs and other access methodsRESTful HTTP APIAndroid
iOS
JavaScript API
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
.Net
JDBC
ODBC
Supported programming languagesClojure
Java
Java
JavaScript
Objective-C
C#
Java
PHP
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionslimited functionality with using 'rules'Transact SQLyes infoJavauser defined functions in Python
TriggersBy using transaction functionsCallbacks are triggered when data changesnoyesno
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 Partitioninghorizontal and vertical partitioning
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 methodsnononoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes
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
User concepts infoAccess controlnoyes, based on authentication and database rulesyesAccess rights for users, groups and roles according to SQL-standard

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More resources
DatomicFirebase Realtime DatabaseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSplice MachineSQream DB
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