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DBMS > FeatureBase vs. Microsoft Azure Data Explorer vs. Weaviate

System Properties Comparison FeatureBase vs. Microsoft Azure Data Explorer vs. Weaviate

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Editorial information provided by DB-Engines
NameFeatureBase  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Fully managed big data interactive analytics platformAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMSRelational DBMS infocolumn orientedVector DBMS
Secondary database modelsDocument 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
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.52
Rank#153  Overall
#6  Vector DBMS
Websitewww.featurebase.comazure.microsoft.com/­services/­data-explorergithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.featurebase.comdocs.microsoft.com/­en-us/­azure/­data-explorerweaviate.io/­developers/­weaviate
DeveloperMolecula and Pilosa Open Source ContributorsMicrosoftWeaviate B.V.
Initial release201720192019
Current release2022, May 2022cloud service with continuous releases1.19, May 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoGo
Server operating systemsLinux
macOS
hosted
Data schemeyesFixed schema with schema-less datatypes (dynamic)yes, 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-typesyes 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 indexesnoall 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 queriesKusto Query Language (KQL), SQL subsetGraphQL is used as query language
APIs and other access methodsgRPC
JDBC
Kafka Connector
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesJava
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Rno
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes, using Linux fsyncyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAzure Active Directory AuthenticationAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
FeatureBaseMicrosoft Azure Data ExplorerWeaviate
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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FeatureBaseMicrosoft Azure Data ExplorerWeaviate
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