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Fast, easy to use business analytics at 1/10th the cost of traditional BI solutions

What is Amazon Quicksight?

Amazon QuickSight is a fast, cloud-powered business analytics service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data.
Amazon Quicksight is a tool in the Business Intelligence category of a tech stack.

Who uses Amazon Quicksight?

Companies
8 companies use Amazon Quicksight in their tech stacks, including Haymarket Media Asia, MPOWER Financing, and Apli.

Developers
6 developers use Amazon Quicksight.

Why developers like Amazon Quicksight?

Here’s a list of reasons why companies and developers use Amazon Quicksight
Top Reasons
Amazon Quicksight Reviews

Here are some stack decisions, common use cases and reviews by companies and developers who chose Amazon Quicksight in their tech stack.

Julien DeFrance
Julien DeFrance
Full Stack Engineering Manager at ValiMail · | 16 upvotes · 78K views
atSmartZip
Amazon DynamoDB
Ruby
Node.js
AWS Lambda
New Relic
Amazon Elasticsearch Service
Elasticsearch
Superset
Amazon Quicksight
Amazon Redshift
Zapier
Segment
Amazon CloudFront
Memcached
Amazon ElastiCache
Amazon RDS for Aurora
MySQL
Amazon RDS
Amazon S3
Docker
Capistrano
AWS Elastic Beanstalk
Rails API
Rails
Algolia

Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.

Future improvements / technology decisions included:

Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic

As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.

One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.

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Amazon Quicksight Alternatives & Comparisons

What are some alternatives to Amazon Quicksight?
Tableau
Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
DOMO
Domo: business intelligence, data visualization, dashboards and reporting all together. Simplify your big data and improve your business with Domo's agile and mobile-ready platform.
Looker
We've built a unique data modeling language, connections to today's fastest analytical databases, and a service that you can deploy on any infrastructure, and explore on any device. Plus, we'll help you every step of the way.
Metabase
Metabase is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.
Redash
Redash helps you make sense of your data. Connect and query your data sources, build dashboards to visualize data and share them with your company.
See all alternatives

Amazon Quicksight's Stats

- No public GitHub repository available -