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DBMS > Datomic vs. FatDB vs. Microsoft Azure Data Explorer vs. Qdrant

System Properties Comparison Datomic vs. FatDB vs. Microsoft Azure Data Explorer vs. Qdrant

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFatDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonQdrant  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA .NET NoSQL DBMS that can integrate with and extend SQL Server.Fully managed big data interactive analytics platformA high-performance vector database with neural network or semantic-based matching
Primary database modelRelational DBMSDocument store
Key-value store
Relational 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
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score1.53
Rank#145  Overall
#7  Vector DBMS
Websitewww.datomic.comazure.microsoft.com/­services/­data-explorergithub.com/­qdrant/­qdrant
qdrant.tech
Technical documentationdocs.datomic.comdocs.microsoft.com/­en-us/­azure/­data-explorerqdrant.tech/­documentation
DeveloperCognitectFatCloudMicrosoftQdrant
Initial release2012201220192021
Current release1.0.7180, July 2024cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC#Rust
Server operating systemsAll OS with a Java VMWindowshostedDocker
Linux
macOS
Windows
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)schema-free
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-typesNumbers, Strings, Geo, Boolean
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 indexesyesyesall fields are automatically indexedyes infoKeywords, numberic ranges, geo, full-text
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerKusto Query Language (KQL), SQL subsetno
APIs and other access methodsRESTful HTTP API.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Supported programming languagesClojure
Java
C#.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes infovia applicationsYes, possible languages: KQL, Python, R
TriggersBy using transaction functionsyes infovia applicationsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Collection-level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Eventual Consistency, tunable consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
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)yesyesyes
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 controlnono infoCan implement custom security layer via applicationsAzure Active Directory AuthenticationKey-based authentication

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DatomicFatDBMicrosoft Azure Data ExplorerQdrant
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