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DBMS > Apache IoTDB vs. Atos Standard Common Repository vs. Axibase vs. Microsoft Access vs. Titan

System Properties Comparison Apache IoTDB vs. Atos Standard Common Repository vs. Axibase vs. Microsoft Access vs. Titan

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonAxibase  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonTitan  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
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 networksScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationMicrosoft 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.)Titan is a Graph DBMS optimized for distributed clusters.
Primary database modelTime Series DBMSDocument store
Key-value store
Time Series DBMSRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.29
Rank#292  Overall
#25  Time Series DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Websiteiotdb.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositoryaxibase.com/­docs/­atsd/­financewww.microsoft.com/­en-us/­microsoft-365/­accessgithub.com/­thinkaurelius/­titan
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldeveloper.microsoft.com/­en-us/­accessgithub.com/­thinkaurelius/­titan/­wiki
DeveloperApache Software FoundationAtos Convergence CreatorsAxibase CorporationMicrosoftAurelius, owned by DataStax
Initial release20182016201319922012
Current release1.1.0, April 20231703155851902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidcommercial infoBundled with Microsoft OfficeOpen Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJavaC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinuxWindows infoNot a real database server, but making use of DLLsLinux
OS X
Unix
Windows
Data schemeyesSchema and schema-less with LDAP viewsyesyesyes
Typing infopredefined data types such as float or dateyesoptionalyes infoshort, integer, long, float, double, decimal, stringyesyes
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.noyesno
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like query languageyes infobut not compliant to any SQL standardno
APIs and other access methodsJDBC
Native API
LDAPJDBC
Proprietary protocol (Network API)
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages with LDAP bindingsGo
Java
PHP
Python
R
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Clojure
Java
Python
Server-side scripts infoStored proceduresyesnoyesyes infosince Access 2010 using the ACE-engineyes
Triggersyesyesyesyes infosince Access 2010 using the ACE-engineyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infocell divisionShardingnoneyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesSource-replica replicationnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnoyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyesyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnoACID infobut no files for transaction loggingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction loggingyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlyesLDAP bind authenticationno infoa simple user-level security was built in till version Access 2003User authentification and security via Rexster Graph Server

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More resources
Apache IoTDBAtos Standard Common RepositoryAxibaseMicrosoft AccessTitan
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