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DBMS > Firebase Realtime Database vs. GeoMesa vs. SiteWhere vs. Spark SQL

System Properties Comparison Firebase Realtime Database vs. GeoMesa vs. SiteWhere vs. Spark SQL

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Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonGeoMesa  Xexclude from comparisonSiteWhere  Xexclude from comparisonSpark SQL  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.GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.M2M integration platform for persisting/querying time series dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeSpatial DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.64
Rank#39  Overall
#6  Document stores
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitefirebase.google.com/­products/­realtime-databasewww.geomesa.orggithub.com/­sitewhere/­sitewherespark.apache.org/­sql
Technical documentationfirebase.google.com/­docs/­databasewww.geomesa.org/­documentation/­stable/­user/­index.htmlsitewhere1.sitewhere.io/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogle infoacquired by Google 2014CCRi and othersSiteWhereApache Software Foundation
Initial release2012201420102014
Current release5.0.0, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache License 2.0Open Source infoCommon Public Attribution License Version 1.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaJavaScala
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeyespredefined schemeyes
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.nononono
Secondary indexesyesyesnono
SQL infoSupport of SQLnononoSQL-like DML and DDL statements
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
HTTP RESTJDBC
ODBC
Supported programming languagesJava
JavaScript
Objective-C
Java
Python
R
Scala
Server-side scripts infoStored procedureslimited functionality with using 'rules'nono
TriggersCallbacks are triggered when data changesnono
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerSharding infobased on HBaseyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerselectable replication factor infobased on HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
depending on storage layerImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonono
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.depending on storage layernono
User concepts infoAccess controlyes, based on authentication and database rulesyes infodepending on the DBMS used for storageUsers with fine-grained authorization conceptno

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More resources
Firebase Realtime DatabaseGeoMesaSiteWhereSpark SQL
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