DBMS > Drizzle vs. GigaSpaces vs. NCache vs. PouchDB

System Properties Comparison Drizzle vs. GigaSpaces vs. NCache vs. PouchDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

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

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

Document store

Secondary database models

Graph DBMS
Search engine

Document store
Search engine

Using distributed Lucene

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

Score	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

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

Score	2.35
Rank	#116	Overall
	#22	Document stores

Website

www.gigaspaces.com

www.alachisoft.com/ncache

pouchdb.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

www.alachisoft.com/resources/docs

pouchdb.com/guides

Developer

Drizzle project, originally started by Brian Aker

Gigaspaces Technologies

Alachisoft

Apache Software Foundation

Initial release

2008

2000

2005

2012

Current release

7.2.4, September 2012

15.5, September 2020

5.3.3, April 2024

7.1.1, June 2019

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache Version 2; Commercial licenses available

Open Source

Enterprise Edition available

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java, C++, .Net

C#, .NET, .NET Core, Java

JavaScript

Server operating systems

FreeBSD
Linux
OS X

Linux
macOS
Solaris
Windows

Linux
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

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.

XML can be used for describing objects metadata

Secondary indexes

yes

via views

SQL

Support of SQL

yes

with proprietary extensions

SQL-99 for query and DML statements

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

APIs and other access methods

JDBC

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

IDistributedCache
JCache
LINQ
Proprietary native API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

C
C++
Java
PHP

.Net
C++
Java
Python
Scala

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

JavaScript

Server-side scripts

Stored procedures

yes

support for stored procedures with SQL-Server CLR

View functions in JavaScript

Triggers

hooks for callbacks inside the server can be used.

yes, event driven architecture

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes, with selectable consistency level

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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

ACID

optimistic locking and pessimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

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

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Role-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

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

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