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DBMS > Google Cloud Firestore vs. Microsoft Azure Data Explorer vs. NCache vs. Stardog vs. TempoIQ

System Properties Comparison Google Cloud Firestore vs. Microsoft Azure Data Explorer vs. NCache vs. Stardog vs. TempoIQ

Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNCache  Xexclude from comparisonStardog  Xexclude from comparisonTempoIQ infoformerly TempoDB  Xexclude from comparison
TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.
DescriptionCloud 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 platformOpen-Source and Enterprise in-memory Key-Value StoreEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationScalable analytics DBMS for sensor data, provided as a service (SaaS)
Primary database modelDocument storeRelational DBMS infocolumn orientedKey-value storeGraph DBMS
RDF store
Time 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
Document store
Search engine infoUsing distributed Lucene
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.85
Rank#51  Overall
#8  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.94
Rank#195  Overall
#29  Key-value stores
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitefirebase.google.com/­products/­firestoreazure.microsoft.com/­services/­data-explorerwww.alachisoft.com/­ncachewww.stardog.comtempoiq.com (offline)
Technical documentationfirebase.google.com/­docs/­firestoredocs.microsoft.com/­en-us/­azure/­data-explorerwww.alachisoft.com/­resources/­docsdocs.stardog.com
DeveloperGoogleMicrosoftAlachisoftStardog-UnionTempoIQ
Initial release20172019200520102012
Current releasecloud service with continuous releases5.3.3, April 20247.3.0, May 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoEnterprise Edition availablecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentscommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#, .NET, .NET Core, JavaJava
Server operating systemshostedhostedLinux
Windows
Linux
macOS
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)schema-freeschema-free and OWL/RDFS-schema supportschema-free
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-typespartial infoSupported data types are Lists, Queues, Hashsets, Dictionary and Counteryesyes
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.noyesnono infoImport/export of XML data possibleno
Secondary indexesyesall fields are automatically indexedyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetSQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.Yes, compatible with all major SQL variants through dedicated BI/SQL Serverno
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
IDistributedCache
JCache
LINQ
Proprietary native API
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
HTTP API
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
C#
Java
JavaScript infoNode.js
Python
Ruby
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud FunctionsYes, possible languages: KQL, Python, Rno infosupport for stored procedures with SQL-Server CLRuser defined functions and aggregates, HTTP Server extensions in Javano
Triggersyes, with Cloud Functionsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoNotificationsyes infovia event handlersyes infoRealtime Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceyesnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, with selectable consistency levelMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud DataflowSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology
Immediate Consistency in HA-Cluster
Foreign keys infoReferential integritynononoyes inforelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnooptimistic locking and pessimistic lockingACIDno
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.noyesyesno
User concepts infoAccess controlAccess 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 AuthenticationAuthentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)Access rights for users and rolessimple authentication-based access control
More information provided by the system vendor
Google Cloud FirestoreMicrosoft Azure Data ExplorerNCacheStardogTempoIQ infoformerly TempoDB
Specific characteristicsNCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more
Competitive advantagesNCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more
Typical application scenariosNCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more
Key customersBank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more
Market metricsMarket Leader in .NET Distributed Caching since 2005.
» more
Licensing and pricing modelsNCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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More resources
Google Cloud FirestoreMicrosoft Azure Data ExplorerNCacheStardogTempoIQ infoformerly TempoDB
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