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DBMS > Microsoft Azure Table Storage vs. Netezza vs. Solr vs. Weaviate

System Properties Comparison Microsoft Azure Table Storage vs. Netezza vs. Solr vs. Weaviate

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSolr  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsData warehouse and analytics appliance part of IBM PureSystemsA widely used distributed, scalable search engine based on Apache LuceneAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelWide column storeRelational DBMSSearch engineVector DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.04
Rank#77  Overall
#6  Wide column stores
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score1.52
Rank#153  Overall
#5  Vector DBMS
Websiteazure.microsoft.com/­en-us/­services/­storage/­tableswww.ibm.com/­products/­netezzasolr.apache.orggithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationsolr.apache.org/­resources.htmlweaviate.io/­developers/­weaviate
DeveloperMicrosoftIBMApache Software FoundationWeaviate B.V.
Initial release2012200020062019
Current release9.6.1, May 20241.19, May 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infocommercial license available with Weaviate Enterprise
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 systemshostedLinux infoincluded in applianceAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyes infostring, int, float, geo point, date, cross reference, fuzzy references
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 indexesnoyesyes infoAll search fields are automatically indexedyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLnoyesSolr Parallel SQL InterfaceGraphQL is used as query language
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
GraphQL query language
RESTful HTTP/JSON API
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresnoyesJava pluginsno
Triggersnonoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingACIDoptimistic lockingno
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.noyesyes
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesUsers with fine-grained authorization conceptyesAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
Microsoft Azure Table StorageNetezza infoAlso called PureData System for Analytics by IBMSolrWeaviate
Specific characteristicsWeaviate is an open source vector database that is robust, scalable, cloud-native,...
» more
Competitive advantagesFlexible deployment - Free, open source or fully-managed cloud vector database service...
» more
Typical application scenariosAs a database supporting the development of generative AI and semantic search applications...
» more
Key customersAll companies that have data. ​
» more
Market metricsAs of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more
Licensing and pricing modelsWeaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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More resources
Microsoft Azure Table StorageNetezza infoAlso called PureData System for Analytics by IBMSolrWeaviate
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