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DBMS > Apache IoTDB vs. Firebase Realtime Database vs. Google Cloud Datastore vs. MaxDB

System Properties Comparison Apache IoTDB vs. Firebase Realtime Database vs. Google Cloud Datastore vs. MaxDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMaxDB infoformerly named Adabas-D  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkCloud-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 PlatformA robust and reliable RDBMS optimized to run all major SAP solutions
Primary database modelTime Series DBMSDocument storeDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.41
Rank#151  Overall
#14  Time Series DBMS
Score13.43
Rank#39  Overall
#6  Document stores
Score3.98
Rank#70  Overall
#12  Document stores
Score2.11
Rank#115  Overall
#55  Relational DBMS
Websiteiotdb.apache.orgfirebase.google.com/­products/­realtime-databasecloud.google.com/­datastoremaxdb.sap.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlfirebase.google.com/­docs/­databasecloud.google.com/­datastore/­docsmaxdb.sap.com/­documentation
DeveloperApache Software FoundationGoogle infoacquired by Google 2014GoogleSAP, acquired from Software AG (Adabas-D) in 1997
Initial release2018201220081984
Current release1.1.0, April 20237.9.10.12, February 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)hostedhostedAIX
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
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.nononono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like query language (GQL)yes
APIs and other access methodsJDBC
Native API
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
WebDAV
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Java
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
Java
Perl
PHP
Python
Server-side scripts infoStored proceduresyeslimited functionality with using 'rules'using Google App Engineyes
TriggersyesCallbacks are triggered when data changesCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual 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 Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
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.yesnono
User concepts infoAccess controlyesyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Apache IoTDBFirebase Realtime DatabaseGoogle Cloud DatastoreMaxDB infoformerly named Adabas-D
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