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DBMS > Apache IoTDB vs. Microsoft Azure AI Search vs. OceanBase vs. Solr

System Properties Comparison Apache IoTDB vs. Microsoft Azure AI Search vs. OceanBase vs. Solr

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonOceanBase  Xexclude from comparisonSolr  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 FlinkSearch-as-a-service for web and mobile app developmentA distributed, high available RDBMS compatible with Oracle and MySQLA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelTime Series DBMSSearch engineRelational DBMSSearch engine
Secondary database modelsVector DBMSDocument store
Wide column store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score1.57
Rank#149  Overall
#69  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websiteiotdb.apache.orgazure.microsoft.com/­en-us/­services/­searchen.oceanbase.comsolr.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmllearn.microsoft.com/­en-us/­azure/­searchen.oceanbase.com/­docs/­oceanbase-databasesolr.apache.org/­resources.html
DeveloperApache Software FoundationMicrosoftOceanBase infopreviously Alibaba and Ant GroupApache Software Foundation
Initial release2018201520102006
Current release1.1.0, April 2023V14.3.0, April 20249.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoCommercial license availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typing
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.nonoyesyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenoyesSolr Parallel SQL Interface
APIs and other access methodsJDBC
Native API
RESTful HTTP APIJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
Java
JavaScript
Python
Ada infoin MySQL-compatible model
C infoin Oracle- and MySQL- compatible models
C++ infoin Oracle- and MySQL- compatible models
D infoin MySQL-compatible model
Delphi infoin MySQL-compatible model
Eiffel infoin MySQL-compatible model
Erlang infoin MySQL-compatible model
Haskell infoin MySQL-compatible model
Java infoin Oracle- and MySQL- compatible models
JavaScript (Node.js) infoin MySQL-compatible model
Objective-C infoin MySQL-compatible model
OCaml infoin MySQL-compatible model
Perl infoin MySQL-compatible model
PHP infoin MySQL-compatible model
Python infoin MySQL-compatible model
Ruby infoin MySQL-compatible model
Scheme infoin MySQL-compatible model
Tcl infoin MySQL-compatible model
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesnoPL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible modeJava plugins
Triggersyesnoyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoImplicit feature of the cloud servicehorizontal partitioning (by hash, key, range, range columns, list, and list columns)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infoImplicit feature of the cloud serviceMulti-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlyesyes infousing Azure authenticationAccess rights for users, groups and roles according to SQL-standardyes

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More resources
Apache IoTDBMicrosoft Azure AI SearchOceanBaseSolr
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