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Database Tech with Fexingo: SQL, NoSQL, and Data Storage Conversations

Database Tech with Fexingo: SQL, NoSQL, and Data Storage Conversations

Written by: Fexingo
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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 application's read pattern shifts from row-based to columnar? How do you evaluate consistency models without oversimplifying? This is the conversation for data engineers, architects, and technical leaders who need to make informed storage decisions. #SQL #NoSQL #DatabaseTech #DataStorage #PostgreSQL #MongoDB #Snowflake #TimeSeriesDB #GraphDatabase #ColumnarStorage #NewSQL #DataEngineering #Technology #FexingoBusiness #BusinessPodcast #DatabaseArchitecture #DataGravity #Benchmarking Keep every episode free: buymeacoffee.com/fexingo© 2026 Fexingo. All rights reserved. Economics
Episodes
  • Why Write-Ahead Logging Is Critical for Database Durability

    Why Write-Ahead Logging Is Critical for Database Durability
    Jul 28 2026
    Lucas and Luna dive into write-ahead logging (WAL), the mechanism that ensures your database can survive a power failure without losing data. They explain how PostgreSQL, Oracle, and SQL Server implement WAL, the performance trade-offs of synchronous vs asynchronous commit, and how checkpointing keeps the log from growing forever. A practical breakdown of a core ACID property. #WriteAheadLogging #DatabaseDurability #CrashRecovery #PostgreSQL #Oracle #SQLServer #TransactionLog #DatabaseInternals #ACID #GroupCommit #Checkpointing #SynchronousCommit #AsynchronousCommit #DatabaseTech #FexingoBusiness #BusinessPodcast #Technology #DataStorage Keep every episode free: buymeacoffee.com/fexingo
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    6 mins
  • Why Database Partition Pruning Cuts Query Time Dramatically

    Why Database Partition Pruning Cuts Query Time Dramatically
    Jul 27 2026
    Partition pruning is one of the most effective yet underappreciated optimizations in modern databases. In this episode, Lucas and Luna explore how PostgreSQL and BigQuery use partition pruning to reduce a full-table scan of a year's data down to just a single month. They walk through real-world numbers: a 12x reduction in data scanned, and a query that drops from 45 seconds to under 4. Along the way, they discuss how to design partition keys, what happens when pruning fails, and why even cloud data warehouses rely on this technique to keep costs low. A must-listen for anyone running analytical queries on large partitioned tables. #Database #PartitionPruning #QueryOptimization #PostgreSQL #BigQuery #DataEngineering #SQL #Performance #Analytics #Tech #FexingoBusiness #BusinessPodcast #DatabaseTips #DataWarehouse #CloudComputing #CostOptimization #LucasAndLuna #DatabaseTech Keep every episode free: buymeacoffee.com/fexingo
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    9 mins
  • Why Database Merge Joins Beat Hash Joins for Sorted Data

    Why Database Merge Joins Beat Hash Joins for Sorted Data
    Jul 27 2026
    In this episode of Database Tech with Fexingo, Lucas and Luna explore a common yet overlooked optimization: why merge joins can outperform hash joins when both input tables are pre-sorted. Using a concrete PostgreSQL example with a 10-million-row join, they break down the trade-offs in memory pressure, CPU cache behavior, and disk spill avoidance. Lucas argues that modern optimizers often underestimate the cost of building and probing hash tables, especially when the data is physically ordered by an index. They discuss real-world scenarios where switching to a merge join yielded a 4x speedup, and why leaving hints can help. The conversation also touches on the importance of understanding your data's physical order and how tools like EXPLAIN can expose suboptimal plans. Whether you're tuning SQL queries or designing schema, this episode offers a practical look at join algorithm selection. It's a must-listen for database engineers and data analysts looking to squeeze more performance from their queries without hardware upgrades. #Database #MergeJoin #HashJoin #QueryOptimization #Performance #SQL #PostgreSQL #SortMerge #Indexing #OLTP #JoinAlgorithms #MemoryManagement #DiskSpill #DatabaseTech #FexingoBusiness #BusinessPodcast #Tech #DataEngineering Keep every episode free: buymeacoffee.com/fexingo
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    7 mins
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