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DBMS > Microsoft Azure Table Storage vs. Solr vs. TimesTen vs. Vitess

System Properties Comparison Microsoft Azure Table Storage vs. Solr vs. TimesTen vs. Vitess

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonSolr  Xexclude from comparisonTimesTen  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsA widely used distributed, scalable search engine based on Apache LuceneIn-Memory RDBMS compatible to OracleScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelWide column storeSearch engineRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.04
Rank#77  Overall
#6  Wide column stores
Score41.02
Rank#24  Overall
#3  Search engines
Score1.36
Rank#161  Overall
#75  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­storage/­tablessolr.apache.orgwww.oracle.com/­database/­technologies/­related/­timesten.htmlvitess.io
Technical documentationsolr.apache.org/­resources.htmldocs.oracle.com/­database/­timesten-18.1vitess.io/­docs
DeveloperMicrosoftApache Software FoundationOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005The Linux Foundation, PlanetScale
Initial release2012200619982013
Current release9.6.1, May 202411 Release 2 (11.2.2.8.0)15.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGo
Server operating systemshostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Docker
Linux
macOS
Data schemeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingyesyes
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 indexesnoyes infoAll search fields are automatically indexedyesyes
SQL infoSupport of SQLnoSolr Parallel SQL Interfaceyesyes infowith proprietary extensions
APIs and other access methodsRESTful HTTP APIJava API
RESTful HTTP/JSON API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C
C++
Java
PL/SQL
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoJava pluginsPL/SQLyes infoproprietary syntax
Triggersnoyes infoUser configurable commands triggered on index changesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingoptimistic lockingACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyes infoby means of logfiles and checkpointsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesyesfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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More resources
Microsoft Azure Table StorageSolrTimesTenVitess
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