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DBMS > Apache Doris vs. Microsoft Azure Table Storage vs. Riak KV vs. Solr

System Properties Comparison Apache Doris vs. Microsoft Azure Table Storage vs. Riak KV vs. Solr

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRiak KV  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolA Wide Column Store for rapid development using massive semi-structured datasetsDistributed, fault tolerant key-value storeA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSWide column storeKey-value store infowith links between data sets and object tags for the creation of secondary indexesSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.57
Rank#244  Overall
#113  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score4.10
Rank#82  Overall
#9  Key-value stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitedoris.apache.org
github.com/­apache/­doris
azure.microsoft.com/­en-us/­services/­storage/­tablessolr.apache.org
Technical documentationgithub.com/­apache/­doris/­wikiwww.tiot.jp/­riak-docs/­riak/­kv/­latestsolr.apache.org/­resources.html
DeveloperApache Software Foundation, originally contributed from BaiduMicrosoftOpenSource, formerly Basho TechnologiesApache Software Foundation
Initial release2017201220092006
Current release1.2.2, February 20233.2.0, December 20229.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache version 2, commercial enterprise editionOpen 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 languageJavaErlangJava
Server operating systemsLinuxhostedLinux
OS X
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesnoyes 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.nononoyes
Secondary indexesyesnorestrictedyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesnonoSolr Parallel SQL Interface
APIs and other access methodsJDBC
MySQL client
RESTful HTTP APIHTTP API
Native Erlang Interface
Java API
RESTful HTTP/JSON API
Supported programming languagesJava.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functionsnoErlangJava plugins
Triggersnonoyes infopre-commit hooks and post-commit hooksyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingnooptimistic 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.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights based on private key authentication or shared access signaturesyes, using Riak Securityyes

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More resources
Apache DorisMicrosoft Azure Table StorageRiak KVSolr
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