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

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

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 Database Connection Pool Starvation Still Happens in 2026

    Why Database Connection Pool Starvation Still Happens in 2026
    Jun 29 2026
    Even in 2026, database connection pool starvation remains a top production issue. Lucas and Luna revisit why connection pool exhaustion still occurs despite years of best practices, using a real-world example from a mid-sized e-commerce platform that saw cascading failures during a flash sale. They explain the two most common root causes: too-small pools and long-running queries holding connections, and discuss practical fixes like connection timeout tuning, pool monitoring, and query optimization. This episode is a must-listen for back-end engineers and DevOps teams dealing with scaling databases. #DatabaseConnectionPool #ConnectionStarvation #DatabasePerformance #BackendEngineering #DevOps #ScalingDatabases #SQLErrors #ConnectionTimeout #QueryOptimization #EcommerceTech #DatabaseTroubleshooting #TechPodcast #DatabaseTech #FexingoBusiness #BusinessPodcast #2026 #ProductionIssues #DataEngineering Keep every episode free: buymeacoffee.com/fexingo
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    5 mins
  • Why Database Schema Migrations Fail Without Feature Flags

    Why Database Schema Migrations Fail Without Feature Flags
    Jun 28 2026
    Lucas and Luna discuss a painful production outage at a fintech company caused by a database schema migration that ran before the application code was ready. They explain how feature flags can decouple deployment from release, the risks of online DDL tools in high-traffic systems, and why many teams still treat migrations as an afterthought. Specific numbers: 47-minute write lock, 12 terabytes of data, 3.2 million transactions per minute. A practical episode for engineers who want to sleep better on deployment nights. #Database #SchemaMigration #FeatureFlags #OnlineDDL #Fintech #ProductionIncident #WriteLock #DatabaseDesign #DevOps #ControlledDeployment #DataEngineering #Technology #FexingoBusiness #BusinessPodcast #LucasAndLuna #DatabaseBestPractices #MigrationStrategy #ReleaseManagement Keep every episode free: buymeacoffee.com/fexingo
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    8 mins
  • Why Database Multi-Model Designs Are Gaining Traction

    Why Database Multi-Model Designs Are Gaining Traction
    Jun 28 2026
    Lucas and Luna explore why a growing number of organizations are adopting multi-model databases—systems that natively support relational, document, graph, and key-value workloads in a single engine. They examine the driving forces: the rise of polyglot persistence fatigue, the cost savings from eliminating multiple database stacks, and the practical trade-offs in query performance and operational complexity. The episode centers on a case study of a mid-sized e-commerce company that consolidated its data layer from four separate databases into one multi-model system running ArangoDB, cutting infrastructure costs by 40% while maintaining sub-50 millisecond query latencies for 90% of their workloads. Lucas explains how the technology has matured since the early days of MongoDB and Couchbase, and Luna presses on where single-model specialists still outperform. They close by discussing when a multi-model approach makes sense—and when it's a trap. #MultiModelDatabase #ArangoDB #PolyglotPersistence #DatabaseConsolidation #NoSQL #GraphDatabase #DocumentStore #KeyValueStore #InfrastructureCost #QueryPerformance #Technology #DataEngineering #CloudMigration #DatabaseArchitecture #FexingoBusiness #BusinessPodcast #TechTrends2026 #DataStorage Keep every episode free: buymeacoffee.com/fexingo
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    11 mins
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