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DBMS > Datomic vs. Firebase Realtime Database vs. Microsoft Azure AI Search vs. Splice Machine

System Properties Comparison Datomic vs. Firebase Realtime Database vs. Microsoft Azure AI Search vs. Splice Machine

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSplice Machine  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.Search-as-a-service for web and mobile app developmentOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument storeSearch engineRelational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score5.59
Rank#63  Overall
#7  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.datomic.comfirebase.google.com/­products/­realtime-databaseazure.microsoft.com/­en-us/­services/­searchsplicemachine.com
Technical documentationdocs.datomic.comfirebase.google.com/­docs/­databaselearn.microsoft.com/­en-us/­azure/­searchsplicemachine.com/­how-it-works
DeveloperCognitectGoogle infoacquired by Google 2014MicrosoftSplice Machine
Initial release2012201220152014
Current release1.0.6735, June 2023V13.1, March 2021
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureJava
Server operating systemsAll OS with a Java VMhostedhostedLinux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 SQLnononoyes
APIs and other access methodsRESTful HTTP APIAndroid
iOS
JavaScript API
RESTful HTTP API
RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
Java
Java
JavaScript
Objective-C
C#
Java
JavaScript
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionslimited functionality with using 'rules'noyes infoJava
TriggersBy using transaction functionsCallbacks are triggered when data changesnoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes infoImplicit feature of the cloud serviceMulti-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 ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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 developmentnoyes
User concepts infoAccess controlnoyes, based on authentication and database rulesyes infousing Azure authenticationAccess rights for users, groups and roles according to SQL-standard

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More resources
DatomicFirebase Realtime DatabaseMicrosoft Azure AI SearchSplice Machine
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