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DBMS > eXtremeDB vs. Heroic vs. Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. Weaviate

System Properties Comparison eXtremeDB vs. Heroic vs. Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. Weaviate

Editorial information provided by DB-Engines
NameeXtremeDB  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionNatively in-memory DBMS with options for persistency, high-availability and clusteringTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platformDatabase as a Service offering with high compatibility to Microsoft SQL ServerAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMSRelational DBMS infocolumn orientedRelational 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
Document store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitewww.mcobject.comgithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­products/­azure-sql/­databasegithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationwww.mcobject.com/­docs/­extremedb.htmspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.microsoft.com/­en-us/­azure/­azure-sqlweaviate.io/­developers/­weaviate
DeveloperMcObjectSpotifyMicrosoftMicrosoftWeaviate B.V.
Initial release20012014201920102019
Current release8.2, 2021cloud service with continuous releasesV121.19, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercialOpen Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++JavaC++Go
Server operating systemsAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedhosted
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yesyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyesyes 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.no infosupport of XML interfaces availablenoyesyesno
Secondary indexesyesyes infovia Elasticsearchall fields are automatically indexedyesyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLyes infowith the option: eXtremeSQLnoKusto Query Language (KQL), SQL subsetyesGraphQL is used as query language
APIs and other access methods.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
GraphQL query language
RESTful HTTP/JSON API
Supported programming languages.Net
C
C#
C++
Java
Lua
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresyesnoYes, possible languages: KQL, Python, RTransact SQLno
Triggersyes infoby defining eventsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, with always 3 replicas availableyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark 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
Immediate Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDno
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyesyesyes
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.yesnonoyes
User concepts infoAccess controlAzure Active Directory Authenticationfine grained access rights according to SQL-standardAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
eXtremeDBHeroicMicrosoft Azure Data ExplorerMicrosoft Azure SQL Database infoformerly SQL AzureWeaviate
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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As a database supporting the development of generative AI and semantic search applications...
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Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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All companies that have data. ​
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Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
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As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
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Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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eXtremeDBHeroicMicrosoft Azure Data ExplorerMicrosoft Azure SQL Database infoformerly SQL AzureWeaviate
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