Real stories from the field, technical insights from daily work, and practical advice based on actual database challenges we've solved in Taiwan's tech sector.
Last week, a manufacturing client's reporting queries were taking 45 seconds. Not ideal when you're trying to make decisions about production schedules. We traced it back to missing indexes on their timestamp columns—something that happens more often than you'd expect.
Read full analysis →A look back at projects and challenges from the past few months—what worked, what didn't, and what we learned along the way.
Moved three years of transaction data from an aging SQL Server setup to a modern PostgreSQL cluster. The tricky part wasn't the data transfer itself—it was making sure their reporting tools still worked correctly afterward. Took about six weeks total, including testing.
A fintech company reached out because their API response times were getting worse. Turns out their database connection pooling was misconfigured, and they had some inefficient join operations in frequently-called stored procedures. Fixed both issues over a weekend.
We ran a disaster recovery drill for a logistics client and discovered their backup restoration process hadn't been tested in over a year. Good news: we found the issue during a test. Bad news: it would've been a disaster in a real emergency. Spent the next month fixing their backup procedures.
Held a two-day session for development teams at a software company in Taipei. Covered practical indexing strategies, query plan analysis, and common pitfalls. The hands-on exercises with real query problems seemed to click better than theoretical explanations.
Database normalization is taught as gospel in school, but real-world applications sometimes need a different approach. We worked with an analytics platform that was grinding to a halt because of excessive joins. Denormalizing their reporting tables cut query times by 70%.
Most monitoring setups generate way too many alerts. You end up ignoring them all. We prefer focusing on a few key metrics that actually predict problems before they happen—things like connection pool saturation and unusual query pattern changes.