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DBMS > Firebase Realtime Database vs. Google Cloud Datastore vs. HarperDB vs. Trafodion

System Properties Comparison Firebase Realtime Database vs. Google Cloud Datastore vs. HarperDB vs. Trafodion

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Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHarperDB  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
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 PlatformUltra-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.Transactional SQL-on-Hadoop DBMS
Primary database modelDocument storeDocument storeDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score15.00
Rank#39  Overall
#6  Document stores
Score4.49
Rank#79  Overall
#12  Document stores
Score0.55
Rank#252  Overall
#38  Document stores
Websitefirebase.google.com/­products/­realtime-databasecloud.google.com/­datastorewww.harperdb.iotrafodion.apache.org
Technical documentationfirebase.google.com/­docs/­databasecloud.google.com/­datastore/­docsdocs.harperdb.io/­docstrafodion.apache.org/­documentation.html
DeveloperGoogle infoacquired by Google 2014GoogleHarperDBApache Software Foundation, originally developed by HP
Initial release2012200820172014
Current release3.1, August 20212.3.0, February 2019
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree community edition availableOpen Source infoApache 2.0
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 languageNode.jsC++, Java
Server operating systemshostedhostedLinux
OS X
Linux
Data schemeschema-freeschema-freedynamic schemayes
Typing infopredefined data types such as float or dateyesyes, details hereyes infoJSON data typesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like data manipulation statementsyes
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
ADO.NET
JDBC
ODBC
Supported programming languagesJava
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.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
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored procedureslimited functionality with using 'rules'using Google App EngineCustom Functions infosince release 3.1Java Stored Procedures
TriggersCallbacks are triggered when data changesCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infothe nodes on which a table resides can be definedyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownoyes infovia user defined functions and HBase
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.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsAtomic execution of specific operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
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)Access rights for users and rolesfine grained access rights according to SQL-standard

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More resources
Firebase Realtime DatabaseGoogle Cloud DatastoreHarperDBTrafodion
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