My TL;DR style notes from articles I read today.

A one size fits all database doesn’t fit anyone

When to consider what type of database:

• Relational: when referential integrity with strong consistency is needed.

• Key-value: when access patterns require low-latency Gets/Puts for known key values.

• Document: when you want developers to use something intuitive.

• Graph: when working with highly connected datasets.

• In-memory: when you need microsecond response times and expect large spikes in traffic coming at any time.

• Search: when you need to index and search semi-structured logs & data.

Full post here, 7 mins read

Bad Practices in Database Design: Are You Making These Mistakes

• Ignoring the purpose of the data
• Poor normalization
• Redundancy
• Bad Referential Integrity
• Not Taking Advantage of DB Engine Features
• Poor Indexing & Naming Conventions

Full post here, 9 mins read

Efficient Software Project Management at its Roots

Common patterns in software projects that are more successful than others:

• Clarity & alignment right from the start on why is the project being taken up, how will the team get it done and what role will each individual play
• Setting milestones that verify if the team is making progress in the right direction or not
• Regular updates with 100% transparency about where each individual and the team really is in the development cycle
• Dependency & risk management in a pragmatic way

Full post here, 8 mins read

I share these TL;DR versions of articles on software engineering that I read every weekday through my newsletter - in.snippets(). Sign up here if you liked what you just read.