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DBMS > Amazon Neptune vs. FatDB vs. Microsoft Azure Data Explorer vs. OpenMLDB

System Properties Comparison Amazon Neptune vs. FatDB vs. Microsoft Azure Data Explorer vs. OpenMLDB

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonFatDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOpenMLDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionFast, reliable graph database built for the cloudA .NET NoSQL DBMS that can integrate with and extend SQL Server.Fully managed big data interactive analytics platformAn open-source machine learning database that provides a feature platform for training and inference
Primary database modelGraph DBMS
RDF store
Document store
Key-value store
Relational DBMS infocolumn orientedTime Series 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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.10
Rank#359  Overall
#36  Time Series DBMS
Websiteaws.amazon.com/­neptuneazure.microsoft.com/­services/­data-exploreropenmldb.ai
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.microsoft.com/­en-us/­azure/­data-exploreropenmldb.ai/­docs/­zh/­main
DeveloperAmazonFatCloudMicrosoft4 Paradigm Inc.
Initial release2017201220192020
Current releasecloud service with continuous releases2024-2 February 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#C++, Java, Scala
Server operating systemshostedWindowshostedLinux
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)Fixed schema
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-typesyes
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 indexesnoyesall fields are automatically indexedyes
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
SQLAlchemy
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C#.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Go
Java
Python
Scala
Server-side scripts infoStored proceduresnoyes infovia applicationsYes, possible languages: KQL, Python, Rno
Triggersnoyes infovia applicationsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.selectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonono
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 infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)no infoCan implement custom security layer via applicationsAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
Amazon NeptuneFatDBMicrosoft Azure Data ExplorerOpenMLDB
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