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DBMS > Apache IoTDB vs. BigObject vs. FatDB vs. Microsoft Access vs. Transbase

System Properties Comparison Apache IoTDB vs. BigObject vs. FatDB vs. Microsoft Access vs. Transbase

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBigObject  Xexclude from comparisonFatDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonTransbase  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
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 FlinkAnalytic DBMS for real-time computations and queriesA .NET NoSQL DBMS that can integrate with and extend SQL Server.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 resource-optimized, high-performance, universally applicable RDBMS
Primary database modelTime Series DBMSRelational DBMS infoa hierachical model (tree) can be imposedDocument store
Key-value store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websiteiotdb.apache.orgbigobject.iowww.microsoft.com/­en-us/­microsoft-365/­accesswww.transaction.de/­en/­products/­transbase.html
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.bigobject.iodeveloper.microsoft.com/­en-us/­accesswww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software FoundationBigObject, Inc.FatCloudMicrosoftTransaction Software GmbH
Initial release20182015201219921987
Current release1.1.0, April 20231902 (16.0.11328.20222), March 2019Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availablecommercialcommercial infoBundled with Microsoft Officecommercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#C++C and C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
WindowsWindows infoNot a real database server, but making use of DLLsFreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsno infoVia inetgration in SQL Serveryes infobut not compliant to any SQL standardyes
APIs and other access methodsJDBC
Native API
fluentd
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyesLuayes infovia applicationsyes infosince Access 2010 using the ACE-engineyes
Triggersyesnoyes infovia applicationsyes infosince Access 2010 using the ACE-engineyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnoneselectable replication factornoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
noneEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID infobut no files for transaction loggingyes
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlyesnono infoCan implement custom security layer via applicationsno infoa simple user-level security was built in till version Access 2003fine grained access rights according to SQL-standard

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More resources
Apache IoTDBBigObjectFatDBMicrosoft AccessTransbase
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