Data, Databases & Streaming

Relational & NoSQL databases, search, caches, streams, ETL/ELT, and analytics stacks.

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Inside Data, Databases & Streaming

Relational (SQL) Postgres/MySQL/SQLite tuning, HA/DR, indexing, and query planning. NoSQL & NewSQL Document, key-value, columnar, search, and distributed SQL engines. Search & Relevance Engineering Full-text search, ranking, synonyms, vectors, and hybrid retrieval patterns. Caching & Edge Data KV stores, CDNs, edge runtimes, and latency-first data patterns. Streaming & Queues Event streaming, pub/sub, backpressure, and consumer groups at scale. ORMs & Migrations Type-safe models, schema diffs, seed data, and multi-tenant strategies. Data Engineering & Analytics Pipelines, orchestration, dbt, warehouses, BI, and governance/lineage.

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Latest in Data, Databases & Streaming


dev.to > codenameone > faster-maps-chasing-swiss-speed-pl7

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44+ min ago   (974+ words) ParparVM fixes pathological map misses and extends tagged boxed values. Probe counts, allocation coverage, and regressions show where ordinary Java collections became cheaper. Tagged with java, mobile, android, ios....


dev.to > devanshu_patil > a-fast-vps-is-useless-if-you-cant-explain-why-its-slow-40jo

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dev.to > seolith > building-foxyinvoice-chapter-4-multi-tenancy-data-security-the-vault-l79

Building FoxyInvoice — Chapter 4: Multi-tenancy & data security — the vault

1+ hour, 59+ min ago   (314+ words) This series is written in the open, from a real production system. This chapter is the vault: identity, isolation, authorization, and the tests that prove it holds. [All chapters and diagrams live in the public repo.] Solo developers imagine hackers....


dev.to > joseph_mwangi_3ae1f57a132 > window-functions-vs-aggregate-functions-in-sql-a-beginner-friendly-guide-i72

Window Functions vs Aggregate Functions in SQL: A Beginner-Friendly Guide

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dev.to > paganini2008 > easyjpa-type-safe-dynamic-queries-in-three-lines-not-thirty-542e

EasyJPA: Type-Safe Dynamic Queries in Three Lines, Not Thirty

3+ hour, 46+ min ago   (617+ words) Every query is a lambda. Every join has a name. Not a single JPQL string. Here is the whole pitch in one screenshot's worth of code. Same query. Same type safety. Same generated SQL. Step 1 — add the dependency. The current…...


dev.to > nainikmehta > cache-stampede-mitigation-stale-while-revalidate-coalescing-268e

Cache Stampede Mitigation: Stale‑While‑Revalidate & Coalescing

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dev.to > mercie_wahome_819901ac530 > power-bi-data-modelling-relationships-and-joins-pij

Power BI: Data Modelling, Relationships and Joins

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analyticsinsight.net > data-science > what-is-vectorization-in-data-science-how-it-speeds-up-statistical-computing

What is Vectorization in Data Science? How it Speeds Up Statistical Computing

1+ day, 19+ hour ago   (761+ words) Vectorization replaces manual, element-by-element loops with operations that run across entire arrays at once. The speed gain comes from compiled code, CPU features like SIMD, and better memory access, not from shorter syntax alone. The technique has limits: dependent calculations,…...


medium.com > @roshniichharampatil > sql-detectives-solving-business-mysteries-one-query-at-a-time-7a067007370f

SQL Detectives: Solving Business Mysteries One Query At a Time

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urbanmatter.com > how-consumer-apps-stay-responsive-when-everyone-opens-them-at-once

How Consumer Apps Stay Responsive When Everyone Opens Them at Once

1+ day, 14+ hour ago   (1556+ words) At noon, tickets for a major concert go on sale. Thousands of people open the same app, search for seats, refresh availability, and try to pay within minutes. The traffic graph shoots up almost vertically. The hard part is not…...