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DBMS > Amazon DocumentDB vs. Apache IoTDB vs. Microsoft Access vs. Sqrrl

System Properties Comparison Amazon DocumentDB vs. Apache IoTDB vs. Microsoft Access vs. Sqrrl

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
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 FlinkMicrosoft 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.)Adaptable, secure NoSQL built on Apache Accumulo
Primary database modelDocument storeTime Series DBMSRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column 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
Score101.16
Rank#11  Overall
#8  Relational DBMS
Websiteaws.amazon.com/­documentdbiotdb.apache.orgwww.microsoft.com/­en-us/­microsoft-365/­accesssqrrl.com
Technical documentationaws.amazon.com/­documentdb/­resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldeveloper.microsoft.com/­en-us/­access
DeveloperApache Software FoundationMicrosoftAmazon infooriginally Sqrrl Data, Inc.
Initial release2019201819922012
Current release1.1.0, April 20231902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial infoBundled with Microsoft Officecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java
Server operating systemshostedAll OS with a Java VM (>= 1.8)Windows infoNot a real database server, but making use of DLLsLinux
Data schemeschema-freeyesyesschema-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.nono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like query languageyes infobut not compliant to any SQL standardno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
Native API
ADO.NET
DAO
ODBC
OLE DB
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Java
Python
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoyesyes infosince Access 2010 using the ACE-engineno
Triggersnoyesyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneSharding infomaking use of Hadoop
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 replicasnoneselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Integration with Hadoop and Sparknoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACID infobut no files for transaction loggingAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes 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.yes
User concepts infoAccess controlAccess rights for users and rolesyesno infoa simple user-level security was built in till version Access 2003Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Amazon DocumentDBApache IoTDBMicrosoft AccessSqrrl
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