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DBMS > Datomic vs. Google Cloud Firestore vs. Microsoft Azure Data Explorer vs. RDFox

System Properties Comparison Datomic vs. Google Cloud Firestore vs. Microsoft Azure Data Explorer vs. RDFox

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRDFox  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Fully managed big data interactive analytics platformHigh performance knowledge graph and semantic reasoning engine
Primary database modelRelational DBMSDocument storeRelational DBMS infocolumn orientedGraph DBMS
RDF store
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
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.23
Rank#308  Overall
#25  Graph DBMS
#14  RDF stores
Websitewww.datomic.comfirebase.google.com/­products/­firestoreazure.microsoft.com/­services/­data-explorerwww.oxfordsemantic.tech
Technical documentationdocs.datomic.comfirebase.google.com/­docs/­firestoredocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oxfordsemantic.tech
DeveloperCognitectGoogleMicrosoftOxford Semantic Technologies
Initial release2012201720192017
Current release1.0.6735, June 2023cloud service with continuous releases6.0, Septermber 2022
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++
Server operating systemsAll OS with a Java VMhostedhostedLinux
macOS
Windows
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yes infoRDF schemas
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.nonoyes
Secondary indexesyesyesall fields are automatically indexed
SQL infoSupport of SQLnonoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsRESTful HTTP APIAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
SPARQL 1.1
Supported programming languagesClojure
Java
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
Java
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes, Firebase Rules & Cloud FunctionsYes, possible languages: KQL, Python, R
TriggersBy using transaction functionsyes, with Cloud Functionsyes 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 service
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.replication via a shared file system
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud DataflowSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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 controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Azure Active Directory AuthenticationRoles, resources, and access types

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More resources
DatomicGoogle Cloud FirestoreMicrosoft Azure Data ExplorerRDFox
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