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DBMS > Apache IoTDB vs. Bangdb vs. Citus vs. Microsoft Azure AI Search

System Properties Comparison Apache IoTDB vs. Bangdb vs. Citus vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBangdb  Xexclude from comparisonCitus  Xexclude from comparisonMicrosoft Azure AI Search  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 FlinkConverged and high performance database for device data, events, time series, document and graphScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLSearch-as-a-service for web and mobile app development
Primary database modelTime Series DBMSDocument store
Graph DBMS
Time Series DBMS
Relational DBMSSearch engine
Secondary database modelsSpatial DBMSDocument storeVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Websiteiotdb.apache.orgbangdb.comwww.citusdata.comazure.microsoft.com/­en-us/­services/­search
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.bangdb.comdocs.citusdata.comlearn.microsoft.com/­en-us/­azure/­search
DeveloperApache Software FoundationSachin Sinha, BangDBMicrosoft
Initial release2018201220102015
Current release1.1.0, April 2023BangDB 2.0, October 20218.1, December 2018V1
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSD 3Open Source infoAGPL, commercial license also availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++C
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinuxhosted
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsyesyes
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.nonoyes infospecific XML type available, but no XML query functionalityno
Secondary indexesyesyes infosecondary, composite, nested, reverse, geospatialyesyes
SQL infoSupport of SQLSQL-like query languageSQL like support with command line toolyes infostandard, with numerous extensionsno
APIs and other access methodsJDBC
Native API
Proprietary protocol
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
Python
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresyesnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersyesyes, Notifications (with Streaming only)yesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding 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 replicasselectable replication factor, Knob for CAP (enterprise version only)Source-replica replication infoother methods possible by using 3rd party extensionsyes 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
Tunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, run db with in-memory only modenono
User concepts infoAccess controlyesyes (enterprise version only)fine grained access rights according to SQL-standardyes infousing Azure authentication

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More resources
Apache IoTDBBangdbCitusMicrosoft Azure AI Search
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