DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Google Cloud Bigtable vs. Microsoft Azure Table Storage vs. NSDb

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure Table Storage vs. NSDb

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Table Storage  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.A Wide Column Store for rapid development using massive semi-structured datasetsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database modelKey-value store
Wide column store
Wide column storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Websitecloud.google.com/­bigtableazure.microsoft.com/­en-us/­services/­storage/­tablesnsdb.io
Technical documentationcloud.google.com/­bigtable/­docsnsdb.io/­Architecture
DeveloperGoogleMicrosoft
Initial release201520122017
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, Scala
Server operating systemshostedhostedLinux
macOS
Data schemeschema-freeschema-free
Typing infopredefined data types such as float or datenoyesyes: 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.nonono
Secondary indexesnonoall fields are automatically indexed
SQL infoSupport of SQLnonoSQL-like query language
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIgRPC
HTTP REST
WebSocket
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Scala
Server-side scripts infoStored proceduresnonono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding 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 zonesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesUsing 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)Access rights based on private key authentication or shared access signatures

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Google Cloud BigtableMicrosoft Azure Table StorageNSDb
Recent citations in the news

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google expands BigQuery with Gemini, brings vector support to cloud databases
29 February 2024, VentureBeat

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

Working with Azure to Use and Manage Data Lakes
7 March 2024, Simplilearn

Azure Cosmos DB Data Migration tool imports from Azure Table storage | Azure updates
5 May 2015, Microsoft

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
9 July 2021, hackernoon.com

Quick Guide to Azure Storage Pricing
16 May 2023, DevOps.com

How to use Azure Table storage in .Net
14 January 2019, InfoWorld

provided by Google News



Share this page

Featured Products

SingleStore logo

The database to transact, analyze and contextualize your data in real time.
Try it today.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here