DBMS > Amazon CloudSearch vs. MySQL vs. OrigoDB vs. Pinecone

System Properties Comparison Amazon CloudSearch vs. MySQL vs. OrigoDB vs. Pinecone

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Editorial information provided by DB-Engines

Name

Description

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

Widely used open source RDBMS

A fully ACID in-memory object graph database

A managed, cloud-native vector database

Primary database model

Search engine

Relational DBMS

Key/Value like access via memcached API

Document store
Object oriented DBMS

Vector DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Website

aws.amazon.com/cloudsearch

www.mysql.com

origodb.com

www.pinecone.io

Technical documentation

docs.aws.amazon.com/cloudsearch

dev.mysql.com/doc

origodb.com/docs

docs.pinecone.io/docs/overview

Developer

Amazon

Oracle

since 2010, originally MySQL AB, then Sun

Robert Friberg et al

Pinecone Systems, Inc

Initial release

2012

1995

2009

under the name LiveDB

2019

Current release

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C and C++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

hosted

Data scheme

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

String, Number, Boolean

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

can be achieved using .NET

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API
HTTP API
LINQ

RESTful HTTP API

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net

Python

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

depending on model

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Users with fine-grained authorization concept

no user groups or roles

Role based authorization

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