DBMS > HBase vs. Machbase Neo vs. NCache vs. Oracle NoSQL

System Properties Comparison HBase vs. Machbase Neo vs. NCache vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

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

TimeSeries DBMS for AIoT and BigData

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

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Wide column store

Time Series DBMS

Key-value store

Document store
Key-value store
Relational DBMS

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Website

hbase.apache.org

machbase.com

www.alachisoft.com/ncache

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

hbase.apache.org/book.html

machbase.com/dbms

www.alachisoft.com/resources/docs

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Machbase

Alachisoft

Oracle

Initial release

2008

2013

2005

2011

Current release

2.3.4, January 2021

V8.0, August 2023

5.3.3, April 2024

24.1, May 2024

License

Commercial or Open Source

Open Source

Apache version 2

commercial

free test version available

Open Source

Enterprise Edition available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C#, .NET, .NET Core, Java

Java

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux
macOS
Windows

Linux
Windows

Linux
Solaris SPARC/x86

Data scheme

schema-free, schema definition possible

yes

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes

partial

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

optional

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 language

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

SQL-like DML and DDL statements

APIs and other access methods

Java API
RESTful HTTP API
Thrift

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

IDistributedCache
JCache
LINQ
Proprietary native API

RESTful HTTP API

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

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

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

yes, with selectable consistency level

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

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

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

Transaction concepts

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

Single row ACID (across millions of columns)

optimistic locking and pessimistic locking

configurable

ACID within a storage node (=shard)

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

volatile and lookup table

yes

off heap cache

User concepts

Access control

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

simple password-based access control

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

Access rights for users and roles

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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