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DBMS > Datomic vs. Firebase Realtime Database vs. Google Cloud Datastore vs. Hawkular Metrics vs. LokiJS

System Properties Comparison Datomic vs. Firebase Realtime Database vs. Google Cloud Datastore vs. Hawkular Metrics vs. LokiJS

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonLokiJS  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.In-memory JavaScript DBMS
Primary database modelRelational DBMSDocument storeDocument storeTime Series DBMSDocument store
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
Score4.36
Rank#72  Overall
#12  Document stores
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score0.49
Rank#260  Overall
#42  Document stores
Websitewww.datomic.comfirebase.google.com/­products/­realtime-databasecloud.google.com/­datastorewww.hawkular.orggithub.com/­techfort/­LokiJS
Technical documentationdocs.datomic.comfirebase.google.com/­docs/­databasecloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidetechfort.github.io/­LokiJS
DeveloperCognitectGoogle infoacquired by Google 2014GoogleCommunity supported by Red Hat
Initial release20122012200820142014
Current release1.0.7075, December 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialOpen Source infoApache 2.0Open Source
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, ClojureJavaJavaScript
Server operating systemsAll OS with a Java VMhostedhostedLinux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesschema-freeschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereyesno
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.nonononono
Secondary indexesyesyesyesnoyes infovia views
SQL infoSupport of SQLnonoSQL-like query language (GQL)nono
APIs and other access methodsRESTful HTTP APIAndroid
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTJavaScript API
Supported programming languagesClojure
Java
Java
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresyes infoTransaction Functionslimited functionality with using 'rules'using Google App EnginenoView functions in JavaScript
TriggersBy using transaction functionsCallbacks are triggered when data changesCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding infobased on Cassandranone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using Paxosselectable replication factor infobased on Cassandranone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownoyes
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 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.Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
none
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono infoatomic operations within a single collection possible
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)yesyesyesyes infoSerialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.
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 developmentnonoyes
User concepts infoAccess controlnoyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
DatomicFirebase Realtime DatabaseGoogle Cloud DatastoreHawkular MetricsLokiJS
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