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DBMS > Amazon DocumentDB vs. Apache IoTDB vs. IBM Db2 Event Store vs. Microsoft Access

System Properties Comparison Amazon DocumentDB vs. Apache IoTDB vs. IBM Db2 Event Store vs. Microsoft Access

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAn 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.)
Primary database modelDocument storeTime Series DBMSEvent Store
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
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
Websiteaws.amazon.com/­documentdbiotdb.apache.orgwww.ibm.com/­products/­db2-event-storewww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationaws.amazon.com/­documentdb/­resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.ibm.com/­docs/­en/­db2-event-storedeveloper.microsoft.com/­en-us/­access
DeveloperApache Software FoundationIBMMicrosoft
Initial release2019201820171992
Current release1.1.0, April 20232.01902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial infofree developer edition availablecommercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C++
Server operating systemshostedAll OS with a Java VM (>= 1.8)Linux infoLinux, macOS, Windows for the developer additionWindows infoNot a real database server, but making use of DLLs
Data schemeschema-freeyesyesyes
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 indexesyesyesnoyes
SQL infoSupport of SQLnoSQL-like query languageyes infothrough the embedded Spark runtimeyes infobut not compliant to any SQL standard
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
Native API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
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
Server-side scripts infoStored proceduresnoyesyesyes infosince Access 2010 using the ACE-engine
Triggersnoyesnoyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasActive-active shard replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Integration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnonoACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes infobut no files for transaction logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlAccess rights for users and rolesyesfine grained access rights according to SQL-standardno infoa simple user-level security was built in till version Access 2003

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More resources
Amazon DocumentDBApache IoTDBIBM Db2 Event StoreMicrosoft Access
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