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DBMS > Google Cloud Bigtable vs. Google Cloud Datastore vs. Microsoft Azure AI Search vs. NSDb

System Properties Comparison Google Cloud Bigtable vs. Google Cloud Datastore vs. Microsoft Azure AI Search vs. NSDb

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonNSDb  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformSearch-as-a-service for web and mobile app developmentScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database modelKey-value store
Wide column store
Document storeSearch engineTime Series DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score4.36
Rank#72  Overall
#12  Document stores
Score5.52
Rank#59  Overall
#6  Search engines
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Websitecloud.google.com/­bigtablecloud.google.com/­datastoreazure.microsoft.com/­en-us/­services/­searchnsdb.io
Technical documentationcloud.google.com/­bigtable/­docscloud.google.com/­datastore/­docslearn.microsoft.com/­en-us/­azure/­searchnsdb.io/­Architecture
DeveloperGoogleGoogleMicrosoft
Initial release2015200820152017
Current releaseV1
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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, Scala
Server operating systemshostedhostedhostedLinux
macOS
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyes, details hereyesyes: 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.nononono
Secondary indexesnoyesyesall fields are automatically indexed
SQL infoSupport of SQLnoSQL-like query language (GQL)noSQL-like query language
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIgRPC
HTTP REST
WebSocket
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
JavaScript
Python
Java
Scala
Server-side scripts infoStored proceduresnousing Google App Enginenono
TriggersnoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication using Paxosyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate 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
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infousing Azure authentication

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More resources
Google Cloud BigtableGoogle Cloud DatastoreMicrosoft Azure AI SearchNSDb
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