DBMS > Amazon CloudSearch vs. GridGain vs. Oracle Rdb vs. PouchDB vs. SQLite

System Properties Comparison Amazon CloudSearch vs. GridGain vs. Oracle Rdb vs. PouchDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

GridGain is an in-memory computing platform, built on Apache Ignite

JavaScript DBMS with an API inspired by CouchDB

Widely used embeddable, in-process RDBMS

Primary database model

Search engine

Key-value store
Relational DBMS

Relational DBMS

Document store

Relational DBMS

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

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/cloudsearch

www.gridgain.com

www.oracle.com/database/technologies/related/rdb.html

pouchdb.com

www.sqlite.org

Technical documentation

docs.aws.amazon.com/cloudsearch

www.gridgain.com/docs/index.html

www.oracle.com/database/technologies/related/rdb-doc.html

pouchdb.com/guides

www.sqlite.org/docs.html

Developer

Amazon

GridGain Systems, Inc.

Oracle, originally developed by Digital Equipment Corporation (DEC)

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2012

2007

1984

2012

2000

Current release

GridGain 8.5.1

7.4.1.1, 2021

7.1.1, June 2019

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Public Domain

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

JavaScript

Server operating systems

hosted

Linux
OS X
Solaris
Windows

HP Open VMS

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

server-less

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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.

yes

Secondary indexes

yes

all search fields are automatically indexed

yes

via views

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

View functions in JavaScript

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes (replicated cache)

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

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

authentication via encrypted signatures

Security Hooks for custom implementations

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