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DBMS > Elasticsearch vs. Microsoft Azure Data Explorer vs. WakandaDB vs. Weaviate

System Properties Comparison Elasticsearch vs. Microsoft Azure Data Explorer vs. WakandaDB vs. Weaviate

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonWakandaDB  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricFully managed big data interactive analytics platformWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access dataAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelSearch engineRelational DBMS infocolumn orientedObject oriented DBMSVector DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitewww.elastic.co/­elasticsearchazure.microsoft.com/­services/­data-explorerwakanda.github.iogithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerwakanda.github.io/­docweaviate.io/­developers/­weaviate
DeveloperElasticMicrosoftWakanda SASWeaviate B.V.
Initial release2010201920122019
Current release8.6, January 2023cloud service with continuous releases2.7.0 (April 29, 2019), April 20191.19, May 2023
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialOpen Source infoAGPLv3, extended commercial license availableOpen Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, JavaScriptGo
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentFixed schema with schema-less datatypes (dynamic)yesyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes 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.noyesnono
Secondary indexesyes infoAll search fields are automatically indexedall fields are automatically indexedyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetnoGraphQL is used as query language
APIs and other access methodsJava API
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIGraphQL query language
RESTful HTTP/JSON API
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
JavaScriptJavaScript / TypeScript
Python
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, Ryesno
Triggersyes infoby using the 'percolation' featureyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop ConnectorSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
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.Memcached and Redis integrationnonoyes
User concepts infoAccess controlAzure Active Directory AuthenticationyesAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
ElasticsearchMicrosoft Azure Data ExplorerWakandaDBWeaviate
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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ElasticsearchMicrosoft Azure Data ExplorerWakandaDBWeaviate
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