Datasource - Best Practices

Question & Answer
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1

Hi Everyone,

I have been using Amazon QuickSight for creating datasets, analyses, and dashboards, where I am directly connecting to a PostgreSQL database as my primary data source. I am reaching out to the community to get insights and best practices when it comes to choosing the right data sources for QuickSight.

What I am specifically seeking guidance on includes:

  • Best practices for selecting a data source in QuickSight.
  • Guidelines or factors to consider when choosing the most appropriate data source for performance and scalability.
  • Any recommendations or considerations that should be taken into account for managing data sources effectively.

I would greatly appreciate any advice, experiences, or resources that could help improve my understanding and approach to working with QuickSight data sources

Regards,

2

Hi @rahmadieh

First i think you are talking about data base not data source, right? Because for data source it is either direct query or SPICE.

Best practices for selecting a data source in QuickSight.

It depends from which direction you are looking and the usage.

  1. Limitation due QuickSight data base interfaces.
  2. Depends on the use case (high storage vs. high usage etc)
  3. Maybe you will use the database with some other services to.
  4. etc

Guidelines or factors to consider when choosing the most appropriate data source for performance and scalability.

Every data base has a different pricing. It always depends on the use case.

  1. Cost
  2. Number of queries
  3. Number of user

Any recommendations or considerations that should be taken into account for managing data sources effectively.

What do you mean by managing data sources?

BR

3

Hi @rahmadieh,
It’s been awhile since we last heard from you, did you have any additional questions regarding your initial topic?

If we do not hear back within the next 3 business days, I’ll go ahead and close out this topic.

Thank you!

4

Thank you @Brett and @ErikG for your reply.

I wanted to get your input on a topic related to selecting the right data source for use in Amazon QuickSight. Specifically, I am considering the different options available and would appreciate your recommendations on best practices for scalability and performance.

In QuickSight, I can connect to relational databases like PostgreSQL or Oracle. However, there’s also the possibility of connecting directly to Amazon S3. My question is, what would be the best approach to follow when adopting a data source to ensure optimal scalability and performance?

For instance, would it be better to move data from a relational database to S3 and have QuickSight read from there, or should we maintain the connection to PostgreSQL or Oracle directly? This is the part where I need clarification regarding what would be considered a best practice, especially in the context of handling larger datasets and ensuring smooth performance.

I would appreciate your insights or any experiences you might have with similar setups.

5

Hi @rahmadieh,
It’s hard to say what would be the best practice for your case specifically without testing.
If your datasets are large and fairly static, S3 could be more beneficial. S3 is setup to store large volumes of data and QuickSight can leverage other Amazon services like Athena to query data using SQL-like syntax.
Whereas your relational database may be more optimal in handling operations like aggregations and dataset joining in relation to your dataset.

6

Hello Rami,

May be you could also look into this to get a general idea -Best practices for Amazon QuickSight SPICE and direct query mode | AWS Business Intelligence Blog

Hope this gives some direction.

Cheers,
Deep

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