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

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

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonPouchDB  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.)JavaScript DBMS with an API inspired by CouchDB
Primary database modelDocument storeTime Series DBMSEvent Store
Time Series DBMS
Relational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Websiteaws.amazon.com/­documentdbiotdb.apache.orgwww.ibm.com/­products/­db2-event-storewww.microsoft.com/­en-us/­microsoft-365/­accesspouchdb.com
Technical documentationaws.amazon.com/­documentdb/­resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.ibm.com/­docs/­en/­db2-event-storedeveloper.microsoft.com/­en-us/­accesspouchdb.com/­guides
DeveloperApache Software FoundationIBMMicrosoftApache Software Foundation
Initial release20192018201719922012
Current release1.1.0, April 20232.01902 (16.0.11328.20222), March 20197.1.1, June 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial infofree developer edition availablecommercial infoBundled with Microsoft OfficeOpen Source
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C++JavaScript
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 DLLsserver-less, requires a JavaScript environment (browser, Node.js)
Data schemeschema-freeyesyesyesschema-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 indexesyesyesnoyesyes infovia views
SQL infoSupport of SQLnoSQL-like query languageyes infothrough the embedded Spark runtimeyes infobut not compliant to any SQL standardno
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
HTTP REST infoonly for PouchDB Server
JavaScript API
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
JavaScript
Server-side scripts infoStored proceduresnoyesyesyes infosince Access 2010 using the ACE-engineView functions in JavaScript
Triggersnoyesnoyes infosince Access 2010 using the ACE-engineyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingnoneSharding infowith a proxy-based framework, named couchdb-lounge
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 replicationnoneMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Integration with Hadoop and Sparknonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnonoACID infobut no files for transaction loggingno
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 loggingyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
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 2003no

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More resources
Amazon DocumentDBApache IoTDBIBM Db2 Event StoreMicrosoft AccessPouchDB
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