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DBMS > Firebase Realtime Database vs. HarperDB vs. Hive vs. RDFox vs. Spark SQL

System Properties Comparison Firebase Realtime Database vs. HarperDB vs. Hive vs. RDFox vs. Spark SQL

Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonHarperDB  Xexclude from comparisonHive  Xexclude from comparisonRDFox  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.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.data warehouse software for querying and managing large distributed datasets, built on HadoopHigh performance knowledge graph and semantic reasoning engineSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeDocument storeRelational DBMSGraph DBMS
RDF store
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.64
Rank#39  Overall
#6  Document stores
Score0.60
Rank#244  Overall
#38  Document stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitefirebase.google.com/­products/­realtime-databasewww.harperdb.iohive.apache.orgwww.oxfordsemantic.techspark.apache.org/­sql
Technical documentationfirebase.google.com/­docs/­databasedocs.harperdb.io/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedocs.oxfordsemantic.techspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogle infoacquired by Google 2014HarperDBApache Software Foundation infoinitially developed by FacebookOxford Semantic TechnologiesApache Software Foundation
Initial release20122017201220172014
Current release3.1, August 20213.1.3, April 20226.0, Septermber 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoApache Version 2commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageNode.jsJavaC++Scala
Server operating systemshostedLinux
OS X
All OS with a Java VMLinux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-freedynamic schemayesyes infoRDF schemasyes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyesyesyes
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.nonono
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoSQL-like data manipulation statementsSQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
Thrift
RESTful HTTP API
SPARQL 1.1
JDBC
ODBC
Supported programming languagesJava
JavaScript
Objective-C
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C++
Java
PHP
Python
C
Java
Java
Python
R
Scala
Server-side scripts infoStored procedureslimited functionality with using 'rules'Custom Functions infosince release 3.1yes infouser defined functions and integration of map-reduceno
TriggersCallbacks are triggered when data changesnonono
Partitioning methods infoMethods for storing different data on different nodesA table resides as a whole on one (or more) nodes in a clusterShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infothe nodes on which a table resides can be definedselectable replication factorreplication via a shared file systemnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduce
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 ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesAtomic execution of specific operationsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlyes, based on authentication and database rulesAccess rights for users and rolesAccess rights for users, groups and rolesRoles, resources, and access typesno

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More resources
Firebase Realtime DatabaseHarperDBHiveRDFoxSpark SQL
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