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

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

Podcast business
🔄 Data last refreshed 9 hours ago
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Ratings
N/A
Episodes
149
Cadence
7.3 ep/wk
Latest episode
20 hours ago
🎁 Free analysisfor Database Tech with Fexingo: SQL, NoSQL, and Data Storage Conversations

💡 Facts

📤Posts about 7.3× per week.

👥 Audience demographics

Estimated

Modeled from this creator's niche, platform & region — a planning estimate, not connected analytics.

Gender split
Male 69% Female 31%
Age · peak 25-34
13-176%
18-2427%
25-3431%
35-4422%
45+14%
Top geographies
  • United States34%
  • India11%
  • United Kingdom8%
  • Brazil6%
  • Indonesia5%
Likely interests
EntertainmentLifestyleTrending

💚 Brand affinity

Estimated

Brands Database Tech with Fexingo: SQL, NoSQL, and Data Storage Conversations's audience is most likely to respond to — from detected sponsorships in this niche.

Keeps Shopify Betterment Gymshark VanEck Nuveen DBMF Webull Charles Schwab Media WisdomTree

About

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

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