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DBMS > Apache IoTDB vs. Informix vs. Microsoft Access vs. mSQL

System Properties Comparison Apache IoTDB vs. Informix vs. Microsoft Access vs. mSQL

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonInformix  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonmSQL infoMini SQL  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 FlinkA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataMicrosoft 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.)mSQL (Mini SQL) is a simple and lightweight RDBMS
Primary database modelTime Series DBMSRelational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score18.85
Rank#35  Overall
#22  Relational DBMS
Score105.40
Rank#11  Overall
#8  Relational DBMS
Score1.67
Rank#151  Overall
#70  Relational DBMS
Websiteiotdb.apache.orgwww.ibm.com/­products/­informixwww.microsoft.com/­en-us/­microsoft-365/­accesshughestech.com.au/­products/­msql
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
developer.microsoft.com/­en-us/­access
DeveloperApache Software FoundationIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.MicrosoftHughes Technologies
Initial release2018198419921994
Current release1.1.0, April 202314.10.FC5, November 20201902 (16.0.11328.20222), March 20194.4, October 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree developer edition availablecommercial infoBundled with Microsoft Officecommercial infofree licenses can be provided
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++ and JavaC++C
Server operating systemsAll OS with a Java VM (>= 1.8)AIX
HP-UX
Linux
macOS
Solaris
Windows
Windows infoNot a real database server, but making use of DLLsAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes infoSince Version 12.10 support for JSON/BSON datatypesyesyes
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 SQLSQL-like query languageyesyes infobut not compliant to any SQL standardA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggers
APIs and other access methodsJDBC
Native API
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C
C++
Delphi
Java
Perl
PHP
Tcl
Server-side scripts infoStored proceduresyesyesyes infosince Access 2010 using the ACE-engineno
Triggersyesyesyes 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)Shardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
Source-replica replication
nonenone
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
Immediate Consistencynone
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infobut no files for transaction loggingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesno
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.yesyesno
User concepts infoAccess controlyesUsers with fine-grained authentication, authorization, and auditing controlsno infoa simple user-level security was built in till version Access 2003no

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More resources
Apache IoTDBInformixMicrosoft AccessmSQL infoMini SQL
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