DBMS > Amazon DynamoDB vs. Apache Phoenix vs. Machbase Neo vs. NCache

System Properties Comparison Amazon DynamoDB vs. Apache Phoenix vs. Machbase Neo vs. NCache

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

A scale-out RDBMS with evolutionary schema built on Apache HBase

TimeSeries DBMS for AIoT and BigData

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

Primary database model

Document store
Key-value store

Relational DBMS

Time Series DBMS

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	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

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

Website

aws.amazon.com/dynamodb

phoenix.apache.org

machbase.com

www.alachisoft.com/ncache

Technical documentation

docs.aws.amazon.com/dynamodb

phoenix.apache.org

machbase.com/dbms

www.alachisoft.com/resources/docs

Developer

Amazon

Apache Software Foundation

Machbase

Alachisoft

Initial release

2012

2014

2013

2005

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

V8.0, August 2023

5.3.3, April 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

commercial

free test version available

Open Source

Enterprise Edition available

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

Java

C#, .NET, .NET Core, Java

Server operating systems

hosted

Linux
Unix
Windows

Linux
macOS
Windows

Linux
Windows

Data scheme

schema-free

yes

late-bound, schema-on-read capabilities

yes

schema-free

Typing

predefined data types such as float or date

yes

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

yes

SQL-like query language

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

APIs and other access methods

RESTful HTTP API

JDBC

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

IDistributedCache
JCache
LINQ
Proprietary native API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Go
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

Server-side scripts

Stored procedures

user defined functions

support for stored procedures with SQL-Server CLR

Triggers

yes

by integration with AWS Lambda

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

selectable replication factor

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

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

volatile and lookup table

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

simple password-based access control

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

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.