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DBMS > Amazon DocumentDB vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. NSDb

System Properties Comparison Amazon DocumentDB vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. NSDb

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNSDb  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully managed big data interactive analytics platformScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database modelDocument storeKey-value store
Wide column 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.80
Rank#148  Overall
#25  Document stores
Score3.86
Rank#90  Overall
#13  Key-value stores
#7  Wide column stores
Score5.82
Rank#65  Overall
#37  Relational DBMS
Score0.07
Rank#369  Overall
#40  Time Series DBMS
Websiteaws.amazon.com/­documentdbcloud.google.com/­bigtableazure.microsoft.com/­services/­data-explorernsdb.io
Technical documentationaws.amazon.com/­documentdb/­resourcescloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­data-explorernsdb.io/­Architecture
DeveloperGoogleMicrosoft
Initial release2019201520192017
Current releasecloud service with continuous releases
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, Scala
Server operating systemshostedhostedhostedLinux
macOS
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesnoyes 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.nonoyesno
Secondary indexesyesnoall fields are automatically indexedall fields are automatically indexed
SQL infoSupport of SQLnonoKusto Query Language (KQL), SQL subsetSQL-like query language
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
gRPC
HTTP REST
WebSocket
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Scala
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Rno
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsAtomic single-row operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing 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 and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory Authentication

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More resources
Amazon DocumentDBGoogle Cloud BigtableMicrosoft Azure Data ExplorerNSDb
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