DBMS > Amazon Redshift vs. GigaSpaces vs. LevelDB vs. PouchDB vs. VelocityDB

System Properties Comparison Amazon Redshift vs. GigaSpaces vs. LevelDB vs. PouchDB vs. VelocityDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

JavaScript DBMS with an API inspired by CouchDB

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

Document store

Graph DBMS
Object oriented DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

aws.amazon.com/redshift

www.gigaspaces.com

github.com/google/leveldb

pouchdb.com

velocitydb.com

Technical documentation

docs.aws.amazon.com/redshift

docs.gigaspaces.com/latest/landing.html

github.com/google/leveldb/blob/main/doc/index.md

pouchdb.com/guides

velocitydb.com/UserGuide

Developer

Amazon (based on PostgreSQL)

Gigaspaces Technologies

Google

Apache Software Foundation

VelocityDB Inc

Initial release

2012

2000

2011

2012

2011

Current release

15.5, September 2020

1.23, February 2021

7.1.1, June 2019

7.x

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

BSD

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, C++, .Net

C++

JavaScript

Server operating systems

hosted

Linux
macOS
Solaris
Windows

Illumos
Linux
OS X
Windows

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

Any that supports .NET

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

restricted

yes

via views

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-99 for query and DML statements

APIs and other access methods

JDBC
ODBC

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

HTTP REST

only for PouchDB Server
JavaScript API

.Net

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C++
Java
Python
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

JavaScript

.Net

Server-side scripts

Stored procedures

user defined functions

in Python

yes

View functions in JavaScript

Triggers

yes, event driven architecture

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

none

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

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

fine grained access rights according to SQL-standard

Role-based access control

Based on Windows Authentication

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