Dean Hantzis

Founder @ The Ambitious, Node/JS Developer, MySQL Expert, MongoDB Expert

About

Dean has over 18 years of system administration and software development experience. With a Master's in Information Technology Management and having worked for three start-ups reaching public exits, Dean offers a mix of management and technology services.

Services

In-house skills available on demand

Database

Scaling, administration and architecture for MySQL, MongoDB and Postgres.

Web Development

Developing with Node, Javascript, Ionic, and Angular.

Linux Admin

Supporting Ubuntu local and cloud infrastructures.

Cloud Dev & Admin

Managing AWS S3, EC2, IAM, SES, SNS, Heroku, CI, TDD and other processes and services.

Hardware

Assembling and configuring high-performance hardware with Linux when performance is paramount.

Technical Liaison

Helping organizations improve process & communication across Dev, IT, Marketing, Business Dev & Financial teams.

Portfolio

Development Projects

Technical Resolutions

MySQL, MongoDB

Database Performance: Identifying The Problem

Database performance issues can often leave organizations feeling helpless. When databases aren't performing well, I often hear developers blame the database technology itself. Most of the time, this is not the real problem. While some databases may perform better in certain areas, overhauling a tech stack with a different database can often take more time (and money) than optimizing the existing technical assets.

When posed with this problem, we start with analysis using a combination of adhoc monitoring and performance tools. Through the analysis we identify the culprits, which can be concurrency, single query performance, ORM query formulation, hardware IO, CPU, memory, or even network latency. Sometimes the solution is a simple one, but hard for a team immersed in day-to-day technical complexities to easily identify. This is why a fresh set of eyes can be the fastest path towards resolution.

If MySQL or MongoDB performance issues are plaguing your products or services, I can help.

Database Indexing

Can Indexing A DB Table Or Collection Hurt Performance?

The short answer is, absolutely. Every time an index is created, write operations slow down since a new index tree must be maintained. Too many indexes can also impact read operations through bloated IO activity.

A common misconception is that a single query in MySQL can make use of multiple indexes on a single table. Another misconception is that migrating all table indexes into a single composite key will improve performance. Composite keys are valuable when the query patterns call for it, but can also limit the scope of key hits depending on the range of query conditions.

Query analysis is the first step to determining the effectiveness of your existing table/collection indexes. When inefficient indexes are removed, it can improve read and write response times and reduce the storage footprint.