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Hosted by Fexingo · 🇺🇸 US · EN · 103 episodes
Established thought leaders with verified media credentials.
Lucas and Luna explore the landscape of database technology, from relational SQL systems to document-based NoSQL and emerging storage paradigms. Each episode examines a specific database model—columnar stores, graph databases, time-series engines, or serverless SQL—and dissects its architecture, performance characteristics, and real-world tradeoffs. Lucas brings a journalist's rigor, questioning vendor claims and surfacing benchmark data; Luna pushes back with practitioner experience, asking how these systems behave under production loads. Together they compare when PostgreSQL's mature indexing wins over MongoDB's flexible schema, or why Snowflake's cloud-native approach may not suit every analytical workload. The show also probes deeper: the economics of data storage, the rise of NewSQL, and the implications of data gravity. Listeners will walk away understanding not just which database to choose, but why one design philosophy beats another for a given problem. What happens when your
Fexingo hosts Database Tech with Fexingo: SQL, NoSQL, and Data Storage Conversations, a business show with 103 episodes published.
Episode 130 dives deep into a single database index technique—the Bloom filter—and shows how it saves millions of disk seeks per second. Lucas explains how a probabilistic data structure with zero false negatives can che
Lucas and Luna dig into why database cursors cause memory blowups when naive streaming is used instead of proper pagination. Using a real-world example of a Postgres query that crashed an analytics dashboard by fetching
Lucas and Luna dive into database deadlock handling, comparing wait-die and wound-wait schemes. Using a concrete example from PostgreSQL 17's transaction manager, they explain how these protocols prevent deadlocks withou
Lucas and Luna explore HTAP — hybrid transactional-analytical processing — and why it's becoming essential for real-time decision-making. They break down the trade-offs between separate OLTP and OLAP systems versus a uni
Lucas and Luna dive into read-write splitting: why the database's own query planner can't be trusted to route traffic efficiently. They dissect a real-world case where a mid-size e-commerce platform in Berlin suffered ca
In this episode of Database Tech with Fexingo, Lucas and Luna explore a subtle but critical failure mode in distributed databases: sharding without a consistent hash ring. Using the real-world example of a fintech startu
In this episode of Database Tech with Fexingo, Lucas and Luna dive into the overlooked but critical topic of database connection timeouts and adaptive retry logic. They explore why fixed timeouts and naive retries can ca
Episode 123 of Database Tech with Fexingo. Lucas and Luna dissect a production nightmare: CDC pipelines delivering duplicate events to a downstream analytics warehouse. They explain why change data capture without exactl
Lucas and Luna dive into the perils of asynchronous replication by examining a real-world outage at a major social media platform in early 2026. They explain why async replication created a multi-hour inconsistency that
Vector databases are everywhere now, but most teams slap an HNSW index on their embeddings without understanding why it works or when it breaks. Lucas and Luna drill into the Hierarchical Navigable Small World graph stru
Lucas and Luna dig into the neglected art of database compression. While most engineers know run-length encoding for repetitive columns, dictionary encoding often delivers 5x better compression on low-cardinality string
Lucas and Luna dive into the trade-offs between size-tiered and leveled compaction in LSM-tree databases like Cassandra and RocksDB. They explain why choosing the wrong compaction strategy for your workload can lead to w
In this episode, Lucas and Luna dive into why traditional materialized views break under real-time data workloads and how incremental refresh strategies—like PostgreSQL's materialized view CONCURRENTLY or Oracle's FAST R
Episode 117 of Database Tech with Fexingo: Lucas and Luna tackle covering indexes — a specific indexing strategy that can eliminate table lookups entirely. They explain how a typical B-tree index works in a PostgreSQL-li
Episode 116 of Database Tech with Fexingo. Lucas and Luna dive into write skew, a subtle concurrency anomaly that breaks snapshot isolation even when individual transactions are consistent. Using the classic doctor-on-ca
Episode 115 of Database Tech with Fexingo. Lucas and Luna drill into multi-tenant database design, using a real SaaS case: a mid-market CRM that hit a noisy-neighbor crisis when one tenant's bulk import saturated disk I/
Row-level security (RLS) is a powerful feature for multi-tenant databases, but it comes with a hidden cost: query performance can degrade significantly if not implemented carefully. In this episode, Lucas and Luna explor
In this episode of Database Tech with Fexingo, Lucas and Luna dive into log-structured merge trees (LSM trees) and why they underpin modern write-heavy databases like Cassandra, LevelDB, and RocksDB. They unpack the trad
Episode 112 of Database Tech with Fexingo tackles a hidden performance killer: query plan caching. Lucas and Luna unpack why reusing cached plans can lead to catastrophic suboptimal execution as data distributions shift,
In this episode of Database Tech with Fexingo, Lucas and Luna dig into a hidden performance trap in modern databases: JSON schema validation. When you store semi-structured data in columns like PostgreSQL's JSONB or Mong
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Database Tech with Fexingo: SQL, NoSQL, and Data Storage Conversations is hosted by Fexingo. The show is categorised under business and has published 103 episodes.
Database Tech with Fexingo: SQL, NoSQL, and Data Storage Conversations has published 103 episodes.
Database Tech with Fexingo: SQL, NoSQL, and Data Storage Conversations regularly covers business. It sits in the business category.
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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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