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DBMS > Firebase Realtime Database vs. Google Cloud Datastore vs. Hawkular Metrics vs. OpenMLDB vs. OpenQM

System Properties Comparison Firebase Realtime Database vs. Google Cloud Datastore vs. Hawkular Metrics vs. OpenMLDB vs. OpenQM

Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonOpenMLDB  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparison
DescriptionCloud-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.An open-source machine learning database that provides a feature platform for training and inferenceQpenQM is a high-performance, self-tuning, multi-value DBMS
Primary database modelDocument storeDocument storeTime Series DBMSTime Series DBMSMultivalue DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.29
Rank#39  Overall
#6  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.02
Rank#367  Overall
#37  Time Series DBMS
Score0.27
Rank#298  Overall
#10  Multivalue DBMS
Websitefirebase.google.com/­products/­realtime-databasecloud.google.com/­datastorewww.hawkular.orgopenmldb.aiwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qm
Technical documentationfirebase.google.com/­docs/­databasecloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guideopenmldb.ai/­docs/­zh/­main
DeveloperGoogle infoacquired by Google 2014GoogleCommunity supported by Red Hat4 Paradigm Inc.Rocket Software, originally Martin Phillips
Initial release20122008201420201993
Current release2024-2 February 20243.4-12
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open SourceOpen Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, Java, Scala
Server operating systemshostedhostedLinux
OS X
Windows
LinuxAIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeFixed schemayes infowith some exceptions
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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.nonononoyes
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)noyesno
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTJDBC
SQLAlchemy
Supported programming languagesJava
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
C++
Go
Java
Python
Scala
.Net
Basic
C
Java
Objective C
PHP
Python
Server-side scripts infoStored procedureslimited functionality with using 'rules'using Google App Enginenonoyes
TriggersCallbacks are triggered when data changesCallbacks using the Google Apps Engineyes infovia Hawkular Alertingnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on Cassandrahorizontal partitioningyes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on CassandraSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standardAccess rights can be defined down to the item level

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More resources
Firebase Realtime DatabaseGoogle Cloud DatastoreHawkular MetricsOpenMLDBOpenQM infoalso called QM
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