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DBMS > Apache IoTDB vs. Google Cloud Firestore vs. Microsoft Access vs. Oracle Rdb vs. TerarkDB

System Properties Comparison Apache IoTDB vs. Google Cloud Firestore vs. Microsoft Access vs. Oracle Rdb vs. TerarkDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonOracle Rdb  Xexclude from comparisonTerarkDB  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 Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelTime Series DBMSDocument storeRelational DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score7.36
Rank#53  Overall
#9  Document stores
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score1.14
Rank#178  Overall
#80  Relational DBMS
Score0.08
Rank#367  Overall
#56  Key-value stores
Websiteiotdb.apache.orgfirebase.google.com/­products/­firestorewww.microsoft.com/­en-us/­microsoft-365/­accesswww.oracle.com/­database/­technologies/­related/­rdb.htmlgithub.com/­bytedance/­terarkdb
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlfirebase.google.com/­docs/­firestoredeveloper.microsoft.com/­en-us/­accesswww.oracle.com/­database/­technologies/­related/­rdb-doc.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software FoundationGoogleMicrosoftOracle, originally developed by Digital Equipment Corporation (DEC)ByteDance, originally Terark
Initial release20182017199219842016
Current release1.1.0, April 20231902 (16.0.11328.20222), March 20197.4.1.1, 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infoBundled with Microsoft Officecommercialcommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++
Server operating systemsAll OS with a Java VM (>= 1.8)hostedWindows infoNot a real database server, but making use of DLLsHP Open VMS
Data schemeyesschema-freeyesFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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 indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like query languagenoyes infobut not compliant to any SQL standardyesno
APIs and other access methodsJDBC
Native API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
C++ API
Java API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C++
Java
Server-side scripts infoStored proceduresyesyes, Firebase Rules & Cloud Functionsyes infosince Access 2010 using the ACE-engineno
Triggersyesyes, with Cloud Functionsyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingnonenone
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 replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkUsing Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACID infobut no files for transaction loggingyes, on a single nodeno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.no infoa simple user-level security was built in till version Access 2003no

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More resources
Apache IoTDBGoogle Cloud FirestoreMicrosoft AccessOracle RdbTerarkDB
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