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DBMS > Apache IoTDB vs. IBM Db2 Event Store vs. Microsoft Access vs. Microsoft Azure Table Storage

System Properties Comparison Apache IoTDB vs. IBM Db2 Event Store vs. Microsoft Access vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure Table Storage  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 FlinkDistributed Event Store optimized for Internet of Things use casesMicrosoft 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 Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelTime Series DBMSEvent Store
Time Series DBMS
Relational DBMSWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websiteiotdb.apache.orgwww.ibm.com/­products/­db2-event-storewww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.ibm.com/­docs/­en/­db2-event-storedeveloper.microsoft.com/­en-us/­access
DeveloperApache Software FoundationIBMMicrosoftMicrosoft
Initial release2018201719922012
Current release1.1.0, April 20232.01902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree developer edition availablecommercial infoBundled with Microsoft Officecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux infoLinux, macOS, Windows for the developer additionWindows infoNot a real database server, but making use of DLLshosted
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesnoyesno
SQL infoSupport of SQLSQL-like query languageyes infothrough the embedded Spark runtimeyes infobut not compliant to any SQL standardno
APIs and other access methodsJDBC
Native API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesyesyes infosince Access 2010 using the ACE-engineno
Triggersyesnoyes 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)ShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasActive-active shard replicationnoneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infobut no files for transaction loggingoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes 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 controlyesfine grained access rights according to SQL-standardno infoa simple user-level security was built in till version Access 2003Access rights based on private key authentication or shared access signatures

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More resources
Apache IoTDBIBM Db2 Event StoreMicrosoft AccessMicrosoft Azure Table Storage
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