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Lucas and Luna sit down at the database-engineering workstation to dissect the world of SQL, NoSQL, and data storage. Each episode takes a single data persistence technology—PostgreSQL, MongoDB, Redis, Cassandra—and walks through its architecture, trade-offs, and real-world deployment patterns. Lucas, with a journalist's precision, charts the evolution from relational schemas to document stores, while Luna presses on cost models, query latency, and the operational headaches of sharding. They avoid vendor cheerleading; instead, they weigh CAP theorem constraints, indexing strategies, and the messy reality of migration. The listener is a developer, data engineer, or technical founder who needs to decide where to put the bytes—and why. Expect no 'best database' declarations, only sharp conversations on consistency, availability, and partition tolerance as they play out in companies like Uber, Netflix, and GitHub. By the end of each episode, you'll understand not just what a database does, but when it breaks.
Unknown Host hosts Database Tech with Fexingo: SQL, NoSQL, and Data Storage Conversations, a general show with 5 episodes published.
In this episode of Database Tech with Fexingo, Lucas and Luna dive into the hidden costs of database timeouts—specifically, why the default timeout values in most application frameworks are dangerously high. Using a real
Episode 32 of Database Tech with Fexingo. Lucas and Luna uncover a subtle but dangerous database vulnerability: security views that accidentally expose sensitive columns like passwords or SSNs through simple tricks like
Episode 31 of Database Tech with Fexingo dives into connection validation — the silent killer of production databases. Lucas and Luna explore why a PostgreSQL pool at a mid-sized e-commerce company crashed during Black F
Lucas and Luna dig into a topic that most developers treat as a checkbox: connection encryption between applications and databases. Using the example of a mid-size fintech that discovered unencrypted PostgreSQL traffic o
Lucas and Luna dig into a quietly dangerous database failure mode: connections that look alive but aren't. When a database pool returns a stale or broken connection, applications can hang, corrupt data, or trigger cascad
Lucas and Luna explore why adding read replicas to scale a database can backfire, using the real-world example of a mid-size e-commerce platform that saw query latency spike 300% after adding replicas. They unpack the hi
Lucas and Luna dive into the often-overlooked world of database connection retry strategies. Using a case study of a mid-size e-commerce platform that lost $200,000 in revenue during a three-hour outage caused by naive r
In this episode of Database Tech with Fexingo, Lucas and Luna dive into database sharding — one of the most powerful but dangerous scaling strategies. They focus on a concrete case: a mid-stage e-commerce company that sh
In this episode of Database Tech with Fexingo, Lucas and Luna continue their deep dive into database connection pool tuning, focusing on the critical parameters that can make or break your application under load. They ex
In this episode, Lucas and Luna dive into the often-overlooked art of tuning database connection pools. They explore why default pool settings can lead to performance bottlenecks, using the example of a fintech app that
Lucas and Luna explain why a default-configured database connection pool can cause more problems than it solves. They walk through a real-world case: a mid-sized e-commerce platform whose connection pool size was set to
Episode 22 of Database Tech with Fexingo: Lucas and Luna dive into the unsung hero of database scalability — partitioning. Using the real-world example of a mid-size e-commerce company that saw query latency spike from 5
Lucas and Luna explore why database connection timeouts—often set too aggressively or too leniently—cause cascading failures in production systems. Using the example of a 2023 outage at a major ticketing platform where a
Episode 20 of Database Tech with Fexingo digs into a specific performance trap: materialized views that look like a silver bullet for slow queries but quietly rot without a proper refresh strategy. Lucas and Luna walk th
In this episode, Lucas and Luna dive into the star schema, the foundational data modeling pattern behind most modern data warehouses. They break down why a single fact table linked to dimension tables can slash query tim
Lucas and Luna unpack the overlooked power of query caching in databases. Using Redis as the primary example, they explore how caching can cut response times from seconds to milliseconds, the difference between write-thr
Episode 17 of Database Tech with Fexingo. Lucas and Luna dig into why connection pooling fails under burst traffic — and what to do about it. They walk through a real-world case: a mid-size e-commerce site that melted do
Episode 16 dives into a production nightmare that's more common than you'd think: connection pool starvation under burst traffic. Lucas walks through a real-world case where a popular e-commerce site's PostgreSQL pool hi
Lucas and Luna dive into the surprisingly common problem of database index bloat — when indexes intended to speed up queries actually slow them down. They explore a real-world case from a mid-sized e-commerce company who
Lucas and Luna dig into a 2025 postmortem from a mid-size fintech that saw its payment API latency spike from 12 milliseconds to over 4 seconds during a routine marketing push. The culprit wasn't the database or the quer
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Database Tech with Fexingo: SQL, NoSQL, and Data Storage Conversations is hosted by Unknown Host. The show is categorised under General and has published 5 episodes.
Database Tech with Fexingo: SQL, NoSQL, and Data Storage Conversations has published 5 episodes.
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Episodes of Database Tech with Fexingo: SQL, NoSQL, and Data Storage Conversations average 9 minutes. a focused format where a clear narrative arc and tight preparation matter most.
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