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DBMS > Microsoft Azure Data Explorer vs. Riak KV vs. Sadas Engine vs. SWC-DB vs. Weaviate

System Properties Comparison Microsoft Azure Data Explorer vs. Riak KV vs. Sadas Engine vs. SWC-DB vs. Weaviate

Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonRiak KV  Xexclude from comparisonSadas Engine  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformDistributed, fault tolerant key-value storeSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsA high performance, scalable Wide Column DBMSAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMS infocolumn orientedKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMSWide column storeVector 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
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websiteazure.microsoft.com/­services/­data-explorerwww.sadasengine.comgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
github.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tiot.jp/­riak-docs/­riak/­kv/­latestwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationweaviate.io/­developers/­weaviate
DeveloperMicrosoftOpenSource, formerly Basho TechnologiesSADAS s.r.l.Alex KashirinWeaviate B.V.
Initial release20192009200620202019
Current releasecloud service with continuous releases3.2.0, December 20228.00.5, April 20211.19, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2, commercial enterprise editioncommercial infofree trial version availableOpen Source infoGPL V3Open Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangC++C++Go
Server operating systemshostedLinux
OS X
AIX
Linux
Windows
Linux
Data schemeFixed schema with schema-less datatypes (dynamic)schema-freeyesschema-freeyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnoyesyes 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.yesnononono
Secondary indexesall fields are automatically indexedrestrictedyesyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetnoyesSQL-like query languageGraphQL is used as query language
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Native Erlang Interface
JDBC
ODBC
Proprietary protocol
Proprietary protocol
Thrift
GraphQL query language
RESTful HTTP/JSON API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
.Net
C
C#
C++
Groovy
Java
PHP
Python
C++JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, RErlangnonono
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infopre-commit hooks and post-commit hooksnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"horizontal partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factornoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynono infolinks between data sets can be storedyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infomanaged by 'Learn by Usage'noyes
User concepts infoAccess controlAzure Active Directory Authenticationyes, using Riak SecurityAccess rights for users, groups and roles according to SQL-standardAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
Microsoft Azure Data ExplorerRiak KVSadas EngineSWC-DB infoSuper Wide Column DatabaseWeaviate
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...
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Typical application scenariosAs a database supporting the development of generative AI and semantic search applications...
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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 Data ExplorerRiak KVSadas EngineSWC-DB infoSuper Wide Column DatabaseWeaviate
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