DBMS > Google Cloud Bigtable vs. gStore vs. HBase vs. NCache

System Properties Comparison Google Cloud Bigtable vs. gStore vs. HBase vs. NCache

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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.

A native Graph DBMS to store and maintain very large RDF datasets.

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

Primary database model

Key-value store
Wide column store

Graph DBMS
RDF store

Wide column store

Key-value store

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.04
Rank	#359	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Website

cloud.google.com/bigtable

en.gstore.cn

hbase.apache.org

www.alachisoft.com/ncache

Technical documentation

cloud.google.com/bigtable/docs

en.gstore.cn/#/enDocs

hbase.apache.org/book.html

www.alachisoft.com/resources/docs

Developer

Google

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Alachisoft

Initial release

2015

2016

2008

2005

Current release

1.2, November 2023

2.3.4, January 2021

5.3.3, April 2024

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

Apache version 2

Open Source

Enterprise Edition available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C#, .NET, .NET Core, Java

Server operating systems

hosted

Linux

Linux
Unix
Windows

using Cygwin

Linux
Windows

Data scheme

schema-free

schema-free and OWL/RDFS-schema support

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

partial

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

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.

Secondary indexes

yes

SQL

Support of SQL

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

APIs and other access methods

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

HTTP API
SPARQL 1.1

Java API
RESTful HTTP API
Thrift

IDistributedCache
JCache
LINQ
Proprietary native API

Supported programming languages

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

C++
Java
JavaScript (Node.js)
PHP
Python

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

Server-side scripts

Stored procedures

yes

Coprocessors in Java

support for stored procedures with SQL-Server CLR

Triggers

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

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 or Eventual Consistency

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

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

yes

Single row ACID (across millions of columns)

optimistic locking and pessimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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)

Users, roles and permissions, Role-Based Access Control (RBAC) supported

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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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