Amazon Redshift vs PostgreSQL

Overview

Amazon Redshift

Stacks1.5K

Followers1.4K

Votes108

PostgreSQL

Stacks103.0K

Followers83.9K

Votes3.6K

GitHub Stars19.0K

Forks5.2K

Amazon Redshift vs PostgreSQL: What are the differences?

Amazon Redshift is a fully managed, cloud-based data warehousing service designed for handling large-scale analytics workloads. PostgreSQL is a powerful open-source relational database management system known for its robustness, flexibility, and extensive feature set. Following are the key differences between Amazon Redshift and PostgreSQL:

Scalability and Performance: Amazon Redshift is specifically designed for handling large-scale data warehousing and analytics workloads. It utilizes columnar storage and parallel query execution to provide fast query performance on massive datasets. PostgreSQL, on the other hand, is a general-purpose relational database management system that can handle a wide range of applications. While PostgreSQL can also handle large datasets, it may not offer the same level of scalability and performance optimizations as Amazon Redshift for data warehousing use cases.
Data Warehousing Capabilities: Amazon Redshift is optimized for data warehousing, offering features such as columnar storage, compression, and advanced query optimization techniques. It provides parallel processing capabilities and supports distributed query execution across multiple nodes to handle complex analytics queries efficiently. PostgreSQL, while capable of handling analytics workloads, may require additional optimizations and tuning to achieve the same level of performance as Redshift in data warehousing scenarios.
Pricing Model: Amazon Redshift follows a pay-as-you-go model, where you pay for the compute resources and storage used. The pricing is based on factors such as the size of the cluster, the number of nodes, and the duration of usage. PostgreSQL, being an open-source database, is typically self-hosted, allowing you to have more control over the cost and infrastructure.
Management and Maintenance: Amazon Redshift is a fully managed service provided by Amazon Web Services (AWS). Redshift also offers features such as automated backups, high availability, and data replication for disaster recovery. PostgreSQL, being an open-source database, requires you to set up and manage the infrastructure yourself. While there are cloud-based managed PostgreSQL services available, they may not offer the same level of automation and integrated management features as Amazon Redshift.
Use Cases: Amazon Redshift is primarily designed for data warehousing and analytics use cases, where fast query performance on large datasets is crucial. It is commonly used for business intelligence, reporting, and data analytics applications. PostgreSQL, on the other hand, is a versatile database that can be used for a wide range of applications, including web applications, content management systems, and transactional systems. It offers a rich set of features and supports complex SQL queries for various use cases beyond data warehousing.

In summary, Amazon Redshift is a specialized data warehousing solution optimized for high-performance analytics on large datasets, while PostgreSQL is a general-purpose relational database that can handle a wide range of applications.

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Advice on Amazon Redshift, PostgreSQL

Kyle

Web Application Developer at Redacted DevWorks

Dec 3, 2019

Decidedon

PostGIS

While there's been some very clever techniques that has allowed non-natively supported geo querying to be performed, it is incredibly slow in the long game and error prone at best.

MySQL finally introduced it's own GEO functions and special indexing operations for GIS type data. I prototyped with this, as MySQL is the most familiar database to me. But no matter what I did with it, how much tuning i'd give it, how much I played with it, the results would come back inconsistent.

It was very disappointing.

I figured, at this point, that SQL Server, being an enterprise solution authored by one of the biggest worldwide software developers in the world, Microsoft, might contain some decent GIS in it.

I was very disappointed.

Postgres is a Database solution i'm still getting familiar with, but I noticed it had no built in support for GIS. So I hilariously didn't pay it too much attention. That was until I stumbled upon PostGIS and my world changed forever.

449k views449k

Comments

George

Student

Mar 18, 2020

Needs adviceon

PostgreSQL

Python

Django

Hello everyone,

Well, I want to build a large-scale project, but I do not know which ORDBMS to choose. The app should handle real-time operations, not chatting, but things like future scheduling or reminders. It should be also really secure, fast and easy to use. And last but not least, should I use them both. I mean PostgreSQL with Python / Django and MongoDB with Node.js? Or would it be better to use PostgreSQL with Node.js?

*The project is going to use React for the front-end and GraphQL is going to be used for the API.

Thank you all. Any answer or advice would be really helpful!

620k views620k

Comments

Navraj

CEO at SuPragma

Apr 16, 2020

Needs adviceon

MySQL

PostgreSQL

I asked my last question incorrectly. Rephrasing it here.

I am looking for the most secure open source database for my project I'm starting: https://github.com/SuPragma/SuPragma/wiki

Which database is more secure? MySQL or PostgreSQL? Are there others I should be considering? Is it possible to change the encryption keys dynamically?

Thanks,

Raj

401k views401k

Comments

Detailed Comparison

Amazon Redshift	PostgreSQL
It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.	PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
Optimized for Data Warehousing- It uses columnar storage, data compression, and zone maps to reduce the amount of IO needed to perform queries. Redshift has a massively parallel processing (MPP) architecture, parallelizing and distributing SQL operations to take advantage of all available resources.;Scalable- With a few clicks of the AWS Management Console or a simple API call, you can easily scale the number of nodes in your data warehouse up or down as your performance or capacity needs change.;No Up-Front Costs- You pay only for the resources you provision. You can choose On-Demand pricing with no up-front costs or long-term commitments, or obtain significantly discounted rates with Reserved Instance pricing.;Fault Tolerant- Amazon Redshift has multiple features that enhance the reliability of your data warehouse cluster. All data written to a node in your cluster is automatically replicated to other nodes within the cluster and all data is continuously backed up to Amazon S3.;SQL - Amazon Redshift is a SQL data warehouse and uses industry standard ODBC and JDBC connections and Postgres drivers.;Isolation - Amazon Redshift enables you to configure firewall rules to control network access to your data warehouse cluster.;Encryption – With just a couple of parameter settings, you can set up Amazon Redshift to use SSL to secure data in transit and hardware-acccelerated AES-256 encryption for data at rest.<br>	-
Statistics
GitHub Stars -	GitHub Stars 19.0K
GitHub Forks -	GitHub Forks 5.2K
Stacks 1.5K	Stacks 103.0K
Followers 1.4K	Followers 83.9K
Votes 108	Votes 3.6K
Pros & Cons
Pros 41 Data Warehousing 27 Scalable 17 SQL 14 Backed by Amazon 5 Encryption	Pros 765 Relational database 511 High availability 439 Enterprise class database 383 Sql 304 Sql + nosql Cons 10 Table/index bloatings
Integrations
SQLite MySQL Oracle PL/SQL	No integrations available

What are some alternatives to Amazon Redshift, PostgreSQL?

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

Related Comparisons

Scalability and Performance: Amazon Redshift is specifically designed for handling large-scale data warehousing and analytics workloads. It utilizes columnar storage and parallel query execution to provide fast query performance on massive datasets. PostgreSQL, on the other hand, is a general-purpose relational database management system that can handle a wide range of applications. While PostgreSQL can also handle large datasets, it may not offer the same level of scalability and performance optimizations as Amazon Redshift for data warehousing use cases.
Data Warehousing Capabilities: Amazon Redshift is optimized for data warehousing, offering features such as columnar storage, compression, and advanced query optimization techniques. It provides parallel processing capabilities and supports distributed query execution across multiple nodes to handle complex analytics queries efficiently. PostgreSQL, while capable of handling analytics workloads, may require additional optimizations and tuning to achieve the same level of performance as Redshift in data warehousing scenarios.
Pricing Model: Amazon Redshift follows a pay-as-you-go model, where you pay for the compute resources and storage used. The pricing is based on factors such as the size of the cluster, the number of nodes, and the duration of usage. PostgreSQL, being an open-source database, is typically self-hosted, allowing you to have more control over the cost and infrastructure.
Management and Maintenance: Amazon Redshift is a fully managed service provided by Amazon Web Services (AWS). Redshift also offers features such as automated backups, high availability, and data replication for disaster recovery. PostgreSQL, being an open-source database, requires you to set up and manage the infrastructure yourself. While there are cloud-based managed PostgreSQL services available, they may not offer the same level of automation and integrated management features as Amazon Redshift.
Use Cases: Amazon Redshift is primarily designed for data warehousing and analytics use cases, where fast query performance on large datasets is crucial. It is commonly used for business intelligence, reporting, and data analytics applications. PostgreSQL, on the other hand, is a versatile database that can be used for a wide range of applications, including web applications, content management systems, and transactional systems. It offers a rich set of features and supports complex SQL queries for various use cases beyond data warehousing.

Amazon Redshift vs PostgreSQL