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DBMS > Firebase Realtime Database vs. Google BigQuery vs. Hawkular Metrics vs. MarkLogic

System Properties Comparison Firebase Realtime Database vs. Google BigQuery vs. Hawkular Metrics vs. MarkLogic

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Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMarkLogic  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.Large scale data warehouse service with append-only tablesHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Operational and transactional Enterprise NoSQL database
Primary database modelDocument storeRelational DBMSTime Series DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.02
Rank#38  Overall
#5  Document stores
Score43.92
Rank#25  Overall
#16  Relational DBMS
Score0.06
Rank#324  Overall
#29  Time Series DBMS
Score9.60
Rank#49  Overall
#7  Document stores
#1  Native XML DBMS
#1  RDF stores
#4  Search engines
Websitefirebase.google.com/­products/­realtime-databasecloud.google.com/­bigquerywww.hawkular.orgwww.marklogic.com
Technical documentationfirebase.google.com/­docs/­databasecloud.google.com/­bigquery/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.marklogic.com
DeveloperGoogle infoacquired by Google 2014GoogleCommunity supported by Red HatMarkLogic Corp.
Initial release2012201020142001
Current release9.0, 2017
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedhostedLinux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeschema-free infoSchema can be enforced
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.nononoyes
Secondary indexesyesnonoyes
SQL infoSupport of SQLnoyesnoyes infoSQL92
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
RESTful HTTP/JSON APIHTTP RESTJava API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Supported programming languagesJava
JavaScript
Objective-C
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
Go
Java
Python
Ruby
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored procedureslimited functionality with using 'rules'user defined functions infoin JavaScriptnoyes infovia XQuery or JavaScript
TriggersCallbacks are triggered when data changesnoyes infovia Hawkular Alertingyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandrayes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesno infoSince BigQuery is designed for querying datanoACID infocan act as a resource manager in an XA/JTA transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes, with Range Indexes
User concepts infoAccess controlyes, based on authentication and database rulesAccess privileges (owner, writer, reader) for whole datasets, not for individual tables infoGoogle Cloud Identity & Access Management (IAM)noRole-based access control at the document and subdocument levels
More information provided by the system vendor
Firebase Realtime DatabaseGoogle BigQueryHawkular MetricsMarkLogic
Specific characteristicsThe MarkLogic Multi-Model Database provides the simplest way to integrate data from...
» more
Competitive advantagesThe main benefit of MarkLogic is simplicity. By making things simpler, MarkLogic...
» more
Typical application scenariosMarkLogic’s main use case is the Operational Data Hub . A Data Hub is useful for...
» more
Key customersMarkLogic has proven results managing mission-critical data with over 1,000 global...
» more
Market metricsMarkLogic is well known within the Fortune 1000, with a strong presence in financial...
» more
Licensing and pricing modelsMarkLogic provides a variety of licenses and cloud services: MarkLogic Data Hub Service...
» more

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More resources
Firebase Realtime DatabaseGoogle BigQueryHawkular MetricsMarkLogic
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