Category: Databases

Rethinking My Vinyl App for MongoDB & Atlas

Alright, here is my thought exercise I did recently switching from PostgreSQL’s normalized structure and moving to harness MongoDB, including the bells and whistles Atlas (the DBaaS) has to offer. This post is taking what I wrote up for my Collector’s Tune Tracker (CTT) and migrating it to MongoDB in a way that makes sense for my eventual deployment of CTT as a real-world app.

Rethinking CTT for MongoDB

Switching from SQL to Mongo isn’t a one-to-one translation. With MongoDB you have to decide smartly what to embed and what to reference. And thanks to Atlas, you’re not just left with a “schema‑less” database you’ve got a whole suite of features that can streamline your development. Let’s break down one possible design for CTT that leverages Atlas features like GraphQL, triggers, and more.

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Reviewing MongoDB Data Workload Migrations

Over the last few years I’ve worked on and led a number of workload projects related to various databases. MongoDB is one of those databases. With some of the ongoing questions I’m asked I found myself wanting to review what the current options are for workload migrations to Mongo DB. Are there new options, is it still the same host of options I’ve reviewed many times before? I wanted to know, so this post is my quick list of findings.

Migrating database workloads isn’t just about moving data it’s about rethinking how your application interacts with data. Depending on your source system and reqs, you can choose from several strategies. These may address not only data migration but also the accompanying application logic, query patterns, and operational practices. Here’s an overview of both popular and lesser-known methods that seem to be the recent, current, and ongoing options:

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Setting Up SQLite on Windows 11: A Guide for Developers

SQLite is a remarkable database engine—lightweight, serverless, and self-contained. Whether you’re building a small-scale project or need a quick, zero-configuration database for testing, SQLite is your go-to solution. But before diving into SQLite with Go or .NET on Windows 11, it’s crucial to understand how Windows 11 is set up by default and what tools you need to make your development environment rock-solid.

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Effective Data Modeling with BSON/JSON: Best Practices and MongoDB Design Patterns

When dealing with BSON/JSON for data modeling, it’s crucial to adhere to certain best practices and leverage design patterns to ensure our data remains organized, consistent, and efficient. Here, we delve into these practices and patterns, starting with general BSON/JSON schema design and then focusing on MongoDB-specific patterns.

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Defining AWS Data Lake vs. Data Warehouse: Choosing the Right Solution

Data Lake vs. Data Warehouse: A Detailed Breakdown with AWS Offerings

When diving into the realms of data storage and management, two terms often come up: data lake and data warehouse. While they might sound similar, they serve distinct purposes and have unique characteristics. Let’s break it down, especially with a focus on what Amazon Web Services (AWS) has to offer.

What is a Data Lake?

A data lake is like a massive reservoir where you can dump data in its raw form. It’s designed to handle structured, semi-structured, and unstructured data. Think of it as a giant pool where data is stored as-is until needed for processing. These lakes are typically built on scalable storage systems such as Hadoop or cloud solutions, making them ideal for big data scenarios.

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