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DBMS > Google Cloud Datastore vs. IBM Db2 vs. Microsoft Azure Data Explorer vs. NSDb vs. RDFox

System Properties Comparison Google Cloud Datastore vs. IBM Db2 vs. Microsoft Azure Data Explorer vs. NSDb vs. RDFox

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNSDb  Xexclude from comparisonRDFox  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformCommon in IBM host environments, 2 different versions for host and Windows/LinuxFully managed big data interactive analytics platformScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesHigh performance knowledge graph and semantic reasoning engine
Primary database modelDocument storeRelational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBRelational DBMS infocolumn orientedTime Series DBMSGraph DBMS
RDF store
Secondary database modelsDocument store
RDF store infoin Db2 LUW (Linux, Unix, Windows)
Spatial DBMS infowith Db2 Spatial Extender
Document 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
Score4.36
Rank#72  Overall
#12  Document stores
Score125.90
Rank#9  Overall
#6  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Websitecloud.google.com/­datastorewww.ibm.com/­products/­db2azure.microsoft.com/­services/­data-explorernsdb.iowww.oxfordsemantic.tech
Technical documentationcloud.google.com/­datastore/­docswww.ibm.com/­docs/­en/­db2docs.microsoft.com/­en-us/­azure/­data-explorernsdb.io/­Architecturedocs.oxfordsemantic.tech
DeveloperGoogleIBMMicrosoftOxford Semantic Technologies
Initial release20081983 infohost version201920172017
Current release12.1, October 2016cloud service with continuous releases6.0, Septermber 2022
License infoCommercial or Open Sourcecommercialcommercial infofree version is availablecommercialOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++Java, ScalaC++
Server operating systemshostedAIX
HP-UX
Linux
Solaris
Windows
z/OS
hostedLinux
macOS
Linux
macOS
Windows
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)yes infoRDF schemas
Typing infopredefined data types such as float or dateyes, details hereyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes: int, bigint, decimal, stringyes
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 indexedall fields are automatically indexed
SQL infoSupport of SQLSQL-like query language (GQL)yesKusto Query Language (KQL), SQL subsetSQL-like query languageno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
gRPC
HTTP REST
WebSocket
RESTful HTTP API
SPARQL 1.1
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Scala
C
Java
Server-side scripts infoStored proceduresusing Google App EngineyesYes, possible languages: KQL, Python, Rno
TriggersCallbacks using the Google Apps Engineyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoonly with Windows/Unix/Linux VersionSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infowith separate tools (MQ, InfoSphere)yes 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 methodsyes infousing Google Cloud DataflownoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardAzure Active Directory AuthenticationRoles, resources, and access types

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More resources
Google Cloud DatastoreIBM Db2 infoformerly named DB2 or IBM Database 2Microsoft Azure Data ExplorerNSDbRDFox
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