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

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

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHypertable  Xexclude from comparisonIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNSDb  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn open source BigTable implementation based on distributed file systems such as HadoopCommon 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 Kubernetes
Primary database modelDocument storeWide column storeRelational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBRelational DBMS infocolumn orientedTime Series DBMS
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
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
Websitecloud.google.com/­datastorewww.ibm.com/­products/­db2azure.microsoft.com/­services/­data-explorernsdb.io
Technical documentationcloud.google.com/­datastore/­docswww.ibm.com/­docs/­en/­db2docs.microsoft.com/­en-us/­azure/­data-explorernsdb.io/­Architecture
DeveloperGoogleHypertable Inc.IBMMicrosoft
Initial release200820091983 infohost version20192017
Current release0.9.8.11, March 201612.1, October 2016cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availablecommercial infofree version is availablecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C and C++Java, Scala
Server operating systemshostedLinux
OS X
Windows infoan inofficial Windows port is available
AIX
HP-UX
Linux
Solaris
Windows
z/OS
hostedLinux
macOS
Data schemeschema-freeschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyes, details herenoyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes: int, bigint, decimal, string
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 indexesyesrestricted infoonly exact value or prefix value scansyesall fields are automatically indexedall fields are automatically indexed
SQL infoSupport of SQLSQL-like query language (GQL)noyesKusto Query Language (KQL), SQL subsetSQL-like query language
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
C++ API
Thrift
ADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
gRPC
HTTP REST
WebSocket
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Perl
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
Server-side scripts infoStored proceduresusing Google App EnginenoyesYes, possible languages: KQL, Python, Rno
TriggersCallbacks using the Google Apps Enginenoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding 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 Paxosselectable replication factor on file system levelyes infowith separate tools (MQ, InfoSphere)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud DataflowyesnoSpark 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.Immediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesUsing Apache Lucene
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
Google Cloud DatastoreHypertableIBM Db2 infoformerly named DB2 or IBM Database 2Microsoft Azure Data ExplorerNSDb
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