Press "Enter" to skip to content

Day: September 6, 2024

Real-Time Streaming in Azure

Published 2024-09-06 by Kevin Feasel

Temidayo Omoniyi takes us through an architecture:

In today’s world, billions of data are generated daily from messaging applications like WhatsApp, financial data like the New York Stock Exchange, or video streaming platforms like YouTube. As a data engineer or solution architect, you are tasked to design a real-time streaming platform that captures the data as they are generated and stored in the necessary storage for decision-making.

This does a great job of going into detail, not only at the architectural level, but also setup and practical implementation.

Leave a Comment

Vacuum, MERGE, and ON CONFLICT Directives

Published 2024-09-06 by Kevin Feasel

Shane Borden looks back at a directive:

I previously blogged about ensuring that the “ON CONFLICT” directive is used in order to avoid vacuum from having to do additional work. You can read the original blog here: Reduce Vacuum by Using “ON CONFLICT” Directive

Now that Postgres has incorporated the “MERGE” functionality into Postgres 15 and above, I wanted to ensure that there was no “strange” behavior as it relates to vacuum when using merge.

Read on to see how things look now.

Leave a Comment

Querying a Fabric SQL Endpoint via Notebook and T-SQL

Published 2024-09-06 by Kevin Feasel

Sandeep Pawar talks about a Spark connector:

I am not sharing anything new. The spark data warehouse connector has been available for a couple months now. It had some bugs, but it seems to be stable now. This connector allows you to query the lakehouse or warehouse endpoint in the Fabric notebook using spark. You can read the documentation for details but below is a quick pattern that you may find handy.

Despite it not being anything new, it is still interesting to see the use case of writing T-SQL instead of Spark SQL.

Leave a Comment

Exploring Azure Data Storage Options

Published 2024-09-06 by Kevin Feasel

Anurag K talks about data storage:

Choosing the right data storage option in Azure is critical for ensuring your applications run efficiently, securely, and cost-effectively. In this blog post, we’ll dive deeper into three key Azure storage services: Blob Storage, File Storage, and Disk Storage. We’ll explore their features, use cases, and provide specific examples to help you understand how to best leverage these services in your cloud environment.

I would note here that within the Blob storage section, you could carve out an explanation of Data Lake Storage Gen2, which starts from Blob storage and then adds hierarchical namespaces (i.e., folders).

Leave a Comment