A developer asked me recently which open data sources he could use for real-time traffic in his application. The list is shorter than he expected, and the main reason is licensing.
Vacuum robots and self-driving taxi robots navigate physical spaces and avoid obstacles. That’s a super broad characterization. The more interesting question is why everything else about them is so different.
I have been writing about shortest-path algorithms and A* heuristics in the context of road networks and pgRouting. But the same graph search concepts show up in a device that millions of people own and never think twice about: the robot vacuum.
While many authors have written about database tuning, systems tuning, or code optimization, I haven't seen any come together to cover the whole stack in such a comprehensive way, targeting both software engineers and database architects.
Having a shared vocabulary across database, software, and infrastructure teams is critical when working together to tune latency issues. I’ve been in many incident rooms where the only report is “the application is slow” and had to unwind a series of questions: What do you mean by slow? Where do you see this? What parts are slow? If everyone in the room had read Enberg’s Latency, solving these kinds of incidents would be much faster.
Query optimization is a critical aspect of database performance tuning. While YugabyteDB’s YSQL API provides powerful tools for analyzing query performance through EXPLAIN plans, sometimes we need to experiment with different indexing strategies without the overhead of actually creating the indexes. This is where HypoPG comes in handy.
As YugabyteDB continues to evolve, its extensive API ecosystem offers powerful capabilities for database management and automation. However, with hundreds of API endpoints across overlapping categories, locating exactly the right API endpoint can be challenging. In this guide, I’ll walk you through several proven strategies for efficiently finding the API endpoints you need, along with real-world examples and pro tips I’ve learned from working with YugabyteDB’s API ecosystem.
After I finished the YugabyteDB universe network mapping example, I started thinking about other things to map. Anything with latitude and longitude will work. College locations from my previous work on the College Scorecard data set were an obvious choice.
One thing that can really wreck your performance in Cassandra and the similar YugabyteDB YCQL is large partitions due to an imbalanced key. Without the robust nodetool commands of Cassandra, it can be challenging to find these large partitions in YugabyteDB.
Today’s global and distributed applications often need to serve user requests from a single data source across different regions. While providing data scaling and protection against network outages, ensuring low-latency access to data is critical for providing a seamless user experience. YugabyteDB, a distributed SQL database, is designed to handle global data workloads efficiently. In this blog post, I’ll share some techniques to optimize read and write latency in a multi-region YugabyteDB cluster.