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DBMS > Datomic vs. FatDB vs. Firebase Realtime Database vs. Google Cloud Datastore vs. Graphite

System Properties Comparison Datomic vs. FatDB vs. Firebase Realtime Database vs. Google Cloud Datastore vs. Graphite

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFatDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGraphite  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA .NET NoSQL DBMS that can integrate with and extend SQL Server.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformData logging and graphing tool for time series data infoThe storage layer (fixed size database) is called Whisper
Primary database modelRelational DBMSDocument store
Key-value store
Document storeDocument storeTime Series 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
Score4.47
Rank#76  Overall
#12  Document stores
Score4.57
Rank#73  Overall
#5  Time Series DBMS
Websitewww.datomic.comfirebase.google.com/­products/­realtime-databasecloud.google.com/­datastoregithub.com/­graphite-project/­graphite-web
Technical documentationdocs.datomic.comfirebase.google.com/­docs/­databasecloud.google.com/­datastore/­docsgraphite.readthedocs.io
DeveloperCognitectFatCloudGoogle infoacquired by Google 2014GoogleChris Davis
Initial release20122012201220082006
Current release1.0.6735, June 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC#Python
Server operating systemsAll OS with a Java VMWindowshostedhostedLinux
Unix
Data schemeyesschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes, details hereNumeric data only
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 indexesyesyesyesyesno
SQL infoSupport of SQLnono infoVia inetgration in SQL ServernoSQL-like query language (GQL)no
APIs and other access methodsRESTful HTTP API.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Sockets
Supported programming languagesClojure
Java
C#Java
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes infovia applicationslimited functionality with using 'rules'using Google App Engineno
TriggersBy using transaction functionsyes infovia applicationsCallbacks are triggered when data changesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersselectable replication factorMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.none
Foreign keys infoReferential integritynononoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyesACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infolocking
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 developmentno
User concepts infoAccess controlnono infoCan implement custom security layer via applicationsyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
DatomicFatDBFirebase Realtime DatabaseGoogle Cloud DatastoreGraphite
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