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DBMS > EsgynDB vs. Microsoft Azure Data Explorer vs. Tkrzw vs. Warp 10 vs. Weaviate

System Properties Comparison EsgynDB vs. Microsoft Azure Data Explorer vs. Tkrzw vs. Warp 10 vs. Weaviate

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonWarp 10  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionFully managed big data interactive analytics platformA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBaseAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMSRelational DBMS infocolumn orientedKey-value storeTime Series DBMSVector 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
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score0.09
Rank#354  Overall
#51  Key-value stores
Score0.08
Rank#358  Overall
#35  Time Series DBMS
Score1.89
Rank#138  Overall
#4  Vector DBMS
Websitewww.esgyn.cnazure.microsoft.com/­services/­data-explorerdbmx.net/­tkrzwwww.warp10.iogithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerwww.warp10.io/­content/­02_Getting_startedweaviate.io/­developers/­weaviate
DeveloperEsgynMicrosoftMikio HirabayashiSenXWeaviate B.V.
Initial release20152019202020152019
Current releasecloud service with continuous releases0.9.3, August 20201.19, May 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoApache License 2.0Open Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++JavaGo
Server operating systemsLinuxhostedLinux
macOS
Linux
OS X
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)schema-freeschema-freeyes, 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-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.noyesnonono
Secondary indexesyesall fields are automatically indexednoyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLyesKusto Query Language (KQL), SQL subsetnonoGraphQL is used as query language
APIs and other access methodsADO.NET
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Jupyter
WebSocket
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Java
Python
Ruby
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresJava Stored ProceduresYes, possible languages: KQL, Python, Rnoyes infoWarpScriptno
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenoneSharding infobased on HBaseSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneselectable replication factor infobased on HBaseyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency infobased on HBaseEventual Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
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.nonoyes infousing specific database classesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAzure Active Directory AuthenticationnoMandatory use of cryptographic tokens, containing fine-grained authorizationsAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
EsgynDBMicrosoft Azure Data ExplorerTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetWarp 10Weaviate
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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EsgynDBMicrosoft Azure Data ExplorerTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetWarp 10Weaviate
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