DBMS > Amazon CloudSearch vs. Amazon Redshift vs. Pinecone vs. Riak TS

System Properties Comparison Amazon CloudSearch vs. Amazon Redshift vs. Pinecone vs. Riak TS

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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

Large scale data warehouse service for use with business intelligence tools

A managed, cloud-native vector database

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

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

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	3.23
Rank	#92	Overall
	#3	Vector DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

aws.amazon.com/cloudsearch

aws.amazon.com/redshift

www.pinecone.io

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.aws.amazon.com/redshift

docs.pinecone.io/docs/overview

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Amazon

Amazon (based on PostgreSQL)

Pinecone Systems, Inc

Open Source, formerly Basho Technologies

Initial release

2012

2019

2015

Current release

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

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

Erlang

Server operating systems

hosted

Linux
OS X

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

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.

Secondary indexes

yes

all search fields are automatically indexed

restricted

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes, limited

APIs and other access methods

HTTP API

JDBC
ODBC

RESTful HTTP API

HTTP API
Native Erlang Interface

Supported programming languages

All languages supporting JDBC/ODBC

Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined functions

in Python

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

links between datasets can be stored

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

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

fine grained access rights according to SQL-standard

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