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

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

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseCloud-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.QpenQM is a high-performance, self-tuning, multi-value DBMS
Primary database modelRelational DBMSDocument storeDocument storeTime Series DBMSMultivalue DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
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
Score0.27
Rank#298  Overall
#10  Multivalue DBMS
Websitephoenix.apache.orgfirebase.google.com/­products/­realtime-databasecloud.google.com/­datastorewww.hawkular.orgwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qm
Technical documentationphoenix.apache.orgfirebase.google.com/­docs/­databasecloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperApache Software FoundationGoogle infoacquired by Google 2014GoogleCommunity supported by Red HatRocket Software, originally Martin Phillips
Initial release20142012200820141993
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.4-12
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0Open Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsLinux
Unix
Windows
hostedhostedLinux
OS X
Windows
AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeschema-freeyes infowith some exceptions
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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 indexesyesyesyesnoyes
SQL infoSupport of SQLyesnoSQL-like query language (GQL)nono
APIs and other access methodsJDBCAndroid
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP REST
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Java
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
.Net
Basic
C
Java
Objective C
PHP
Python
Server-side scripts infoStored proceduresuser defined functionslimited functionality with using 'rules'using Google App Enginenoyes
TriggersnoCallbacks are triggered when data changesCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on Cassandrayes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using Paxosselectable replication factor infobased on Cassandrayes
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual 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
Immediate Consistency
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 TransactionsnoACID
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.yesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights can be defined down to the item level

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More resources
Apache PhoenixFirebase Realtime DatabaseGoogle Cloud DatastoreHawkular MetricsOpenQM infoalso called QM
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