DBMS > Google Cloud Bigtable vs. Microsoft Azure SQL Database vs. NCache vs. NSDb

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure SQL Database vs. NCache vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Database as a Service offering with high compatibility to Microsoft SQL Server

Open-Source and Enterprise in-memory Key-Value Store

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Key-value store
Wide column store

Relational DBMS

Key-value store

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Search engine

Using distributed Lucene

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	3.58
Rank	#92	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	78.40
Rank	#15	Overall
	#10	Relational DBMS

Score	0.98
Rank	#196	Overall
	#29	Key-value stores

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Website

cloud.google.com/bigtable

azure.microsoft.com/en-us/products/azure-sql/database

www.alachisoft.com/ncache

nsdb.io

Technical documentation

cloud.google.com/bigtable/docs

docs.microsoft.com/en-us/azure/azure-sql

www.alachisoft.com/resources/docs

nsdb.io/Architecture

Developer

Google

Microsoft

Alachisoft

Initial release

2015

2010

2005

2017

Current release

V12

5.3.3, April 2024

License

Commercial or Open Source

commercial

Open Source

Enterprise Edition available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

C#, .NET, .NET Core, Java

Java, Scala

Server operating systems

hosted

Linux
Windows

Linux
macOS

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

yes: int, bigint, decimal, string

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

SQL-like query language

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

ADO.NET
JDBC
ODBC

IDistributedCache
JCache
LINQ
Proprietary native API

gRPC
HTTP REST
WebSocket

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
Python

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Java
Scala

Server-side scripts

Stored procedures

Transact SQL

support for stored procedures with SQL-Server CLR

Triggers

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

yes, with always 3 replicas available

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic single-row operations

ACID

optimistic locking and pessimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

More information provided by the system vendor

Specific characteristics

NCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more

Competitive advantages

NCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more

Typical application scenarios

NCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more

Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more

Market metrics

Market Leader in .NET Distributed Caching since 2005.
» more

Licensing and pricing models

NCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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Recent citations in the news

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What is Google Bigtable? | Definition from TechTarget
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31 January 2022, InfoQ.com

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7 September 2016, InfoWorld

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

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