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DBMS > Datomic vs. Microsoft Azure Data Explorer vs. Sphinx vs. Weaviate

System Properties Comparison Datomic vs. Microsoft Azure Data Explorer vs. Sphinx vs. Weaviate

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databasesAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMSRelational DBMS infocolumn orientedSearch engineVector 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
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitewww.datomic.comazure.microsoft.com/­services/­data-explorersphinxsearch.comgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.datomic.comdocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docsweaviate.io/­developers/­weaviate
DeveloperCognitectMicrosoftSphinx Technologies Inc.Weaviate B.V.
Initial release2012201920012019
Current release1.0.6735, June 2023cloud service with continuous releases3.5.1, February 20231.19, May 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoGPL version 2, commercial licence 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

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Implementation languageJava, ClojureC++Go
Server operating systemsAll OS with a Java VMhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesFixed 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-typesnoyes 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 indexesyesall fields are automatically indexedyes infofull-text index on all search fieldsyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)GraphQL is used as query language
APIs and other access methodsRESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocolGraphQL query language
RESTful HTTP/JSON API
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresyes infoTransaction FunctionsYes, possible languages: KQL, Python, Rnono
TriggersBy using transaction functionsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnoyes
User concepts infoAccess controlnoAzure Active Directory AuthenticationnoAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
DatomicMicrosoft Azure Data ExplorerSphinxWeaviate
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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DatomicMicrosoft Azure Data ExplorerSphinxWeaviate
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