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DBMS > Apache IoTDB vs. Atos Standard Common Repository vs. InfinityDB vs. Microsoft Access vs. Microsoft Azure AI Search

System Properties Comparison Apache IoTDB vs. Atos Standard Common Repository vs. InfinityDB vs. Microsoft Access vs. Microsoft Azure AI Search

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonInfinityDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
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 FlinkHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksA Java embedded Key-Value Store which extends the Java Map interfaceMicrosoft 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.)Search-as-a-service for web and mobile app development
Primary database modelTime Series DBMSDocument store
Key-value store
Key-value storeRelational DBMSSearch engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.00
Rank#378  Overall
#57  Key-value stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Websiteiotdb.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositoryboilerbay.comwww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­en-us/­services/­search
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlboilerbay.com/­infinitydb/­manualdeveloper.microsoft.com/­en-us/­accesslearn.microsoft.com/­en-us/­azure/­search
DeveloperApache Software FoundationAtos Convergence CreatorsBoiler Bay Inc.MicrosoftMicrosoft
Initial release20182016200219922015
Current release1.1.0, April 202317034.01902 (16.0.11328.20222), March 2019V1
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial infoBundled with Microsoft Officecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxAll OS with a Java VMWindows infoNot a real database server, but making use of DLLshosted
Data schemeyesSchema and schema-less with LDAP viewsyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyesyes
Typing infopredefined data types such as float or dateyesoptionalyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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.noyesnono
Secondary indexesyesyesno infomanual creation possible, using inversions based on multi-value capabilityyesyes
SQL infoSupport of SQLSQL-like query languagenonoyes infobut not compliant to any SQL standardno
APIs and other access methodsJDBC
Native API
LDAPAccess via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
ADO.NET
DAO
ODBC
OLE DB
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages with LDAP bindingsJavaC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresyesnonoyes infosince Access 2010 using the ACE-engineno
Triggersyesyesnoyes 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)Sharding infocell divisionnonenoneSharding 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 replicasyesnonenoneyes infoImplicit feature of the cloud service
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 Consistency or Eventual Consistency depending on configurationImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integritynonono infomanual creation possible, using inversions based on multi-value capabilityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACID infoOptimistic locking for transactions; no isolation for bulk loadsACID infobut no files for transaction loggingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.yesyesnono
User concepts infoAccess controlyesLDAP bind authenticationnono infoa simple user-level security was built in till version Access 2003yes infousing Azure authentication

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More resources
Apache IoTDBAtos Standard Common RepositoryInfinityDBMicrosoft AccessMicrosoft Azure AI Search
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