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DataFunSummit
DataFunSummit
May 19, 2026 · Databases

Building an AI‑Ready, Multi‑Modal Database Foundation for the Digital Intelligence Era

The talk outlines the AI era’s three major challenges for large language models and data (stability, 3V, resource limits), presents YashanDB’s original theory breakthroughs—including resource‑constrained computing, shared‑cluster performance and adaptive transaction scheduling—details a multi‑modal fusion architecture, introduces the KSA trustworthy knowledge‑engineering framework, and showcases real‑world deployments in smart‑city and energy domains.

AI-Ready Data PlatformEnergy IndustryKnowledge Engineering
0 likes · 16 min read
Building an AI‑Ready, Multi‑Modal Database Foundation for the Digital Intelligence Era
MaGe Linux Operations
MaGe Linux Operations
May 19, 2026 · Databases

How I Reduced a MySQL Slow Query from 3 seconds to 10 milliseconds

This article walks through a real‑world MySQL slow‑query case, showing how to identify the bottleneck with EXPLAIN, design covering and composite indexes, rewrite the SQL, tune InnoDB parameters, and safely deploy the changes, ultimately shrinking execution time from seconds to a few milliseconds.

EXPLAINOptimizationPerformance tuning
0 likes · 32 min read
How I Reduced a MySQL Slow Query from 3 seconds to 10 milliseconds
Ops Community
Ops Community
May 19, 2026 · Databases

10 Common MySQL Index Failure Scenarios – Which Ones Affect You?

This article examines ten typical situations where MySQL indexes become ineffective, explains the underlying reasons such as function usage, implicit type conversion, wildcard LIKE patterns, OR conditions, left‑most prefix violations, small tables, stale statistics, NULL handling, GROUP BY/DISTINCT, and ORDER BY, and provides concrete SQL examples and step‑by‑step remediation techniques to restore optimal query performance.

Database TuningEXPLAINIndex Optimization
0 likes · 32 min read
10 Common MySQL Index Failure Scenarios – Which Ones Affect You?
Su San Talks Tech
Su San Talks Tech
May 17, 2026 · Databases

Why Leading Companies Avoid NULL Values in MySQL

The article explains why major tech companies discourage using NULL in MySQL, covering its meaning as an unknown state, three-valued logic pitfalls such as NOT IN subqueries, index inefficiencies, aggregate function quirks, storage overhead, Java handling issues, and offers practical alternatives like NOT NULL constraints with sensible defaults.

Database DesignIndex OptimizationNULL
0 likes · 11 min read
Why Leading Companies Avoid NULL Values in MySQL
Architecture Digest
Architecture Digest
May 15, 2026 · Databases

Why Alibaba Bans Joins Over Three Tables – A Must‑Know Rule for SQL Engineers

Alibaba’s Java Development Manual mandates that any SQL involving more than three tables must be avoided, a rule that stems from the exponential cost of multi‑table joins in a single‑instance database, prompting engineers to rethink data modeling, adopt denormalization, wide tables, materialized views, CQRS or application‑level assembly instead of relying on complex joins.

AlibabaCQRSDatabase Design
0 likes · 12 min read
Why Alibaba Bans Joins Over Three Tables – A Must‑Know Rule for SQL Engineers
ITPUB
ITPUB
May 14, 2026 · Databases

MySQL 8.0 Reaches End‑of‑Life – What 8.4.9 LTS and 9.7.0 Bring to the Next Era

On April 21, 2026 MySQL 8.0 officially ends its eight‑year run as Oracle releases 8.4.9 LTS and 9.7.0 LTS, introducing long‑term support, new security plugins, Hypergraph Optimizer, JSON Duality Views, cgroup enhancements, and detailed upgrade paths, while warning of severe risks for unpatched 8.0 deployments.

8.4.99.7.0Hypergraph Optimizer
0 likes · 22 min read
MySQL 8.0 Reaches End‑of‑Life – What 8.4.9 LTS and 9.7.0 Bring to the Next Era
21CTO
21CTO
May 14, 2026 · Databases

MySQL 9.7 LTS Launch: First Major Release Since 8.4 Brings Enterprise Features to the Community

Oracle announced MySQL 9.7.0 LTS, the first major LTS since 8.4, introducing community‑available enterprise features such as the Hypergraph optimizer, dynamic data masking, enhanced replication observability, and new operational tools, while addressing community concerns about Oracle’s commitment and recent development slowdown.

Database operationsDynamic data maskingHypergraph Optimizer
0 likes · 8 min read
MySQL 9.7 LTS Launch: First Major Release Since 8.4 Brings Enterprise Features to the Community
Architect's Guide
Architect's Guide
May 14, 2026 · Databases

8 SQL Pitfalls That Can Slow Your Queries 100‑Fold – How to Avoid Them

The article enumerates eight common MySQL query patterns—such as large‑offset LIMIT, implicit type conversion, sub‑query updates, mixed ordering, unnecessary EXISTS, poor condition push‑down, early range reduction, and inefficient intermediate result handling—and shows rewritten SQL that reduces execution time from seconds to milliseconds.

IndexesJoinPerformance
0 likes · 15 min read
8 SQL Pitfalls That Can Slow Your Queries 100‑Fold – How to Avoid Them
Wukong Talks Architecture
Wukong Talks Architecture
May 14, 2026 · Databases

How to Cut a Production MySQL 8.0 LATERAL Query from 3 s to 0.8 s

The article walks through diagnosing a slow MySQL 8.0 query that scans 77,724 rows and performs a costly filesort, then rewrites it with a LATERAL join and a new index, reducing execution time to about 0.75 seconds on 30 k rows while explaining the differences between ordinary subqueries and LATERAL, and highlighting the need for deterministic ordering when timestamps duplicate.

LATERALexecution planindex
0 likes · 8 min read
How to Cut a Production MySQL 8.0 LATERAL Query from 3 s to 0.8 s
ITPUB
ITPUB
May 13, 2026 · Databases

Is the Hype Around Vector Databases a Pseudo‑Demand in the AI Era?

The article questions whether dedicated vector databases are truly needed for AI applications, examining market hype, the rapid emergence of many vector‑DB products, real‑world examples like PostgreSQL pgvector and major vendor integrations, and the hidden costs of data fragmentation and operational complexity.

AIPostgreSQLRAG
0 likes · 15 min read
Is the Hype Around Vector Databases a Pseudo‑Demand in the AI Era?
JD Tech
JD Tech
May 13, 2026 · Databases

Deep Dive into Using JSON Fields in Databases: Practical Lessons and Pitfalls

This article walks through the rationale, common functions, and real‑world case studies of storing and querying JSON columns in a relational database, exposing issues with null handling, batch updates, and dynamic SQL generation, and presents step‑by‑step debugging and robust solutions.

Batch UpdateDatabaseDynamic Queries
0 likes · 11 min read
Deep Dive into Using JSON Fields in Databases: Practical Lessons and Pitfalls
IT Services Circle
IT Services Circle
May 12, 2026 · Databases

How to Diagnose and Resolve Online Slow SQL That Causes CPU Spikes

When a MySQL‑driven application shows sudden CPU spikes, this guide walks through a step‑by‑step process—using top/htop, SHOW PROCESSLIST, enabling slow‑query logs, analyzing EXPLAIN output, killing offending queries, adding appropriate indexes, rewriting joins, and establishing preventive monitoring—to quickly identify and fix the root cause.

CPU SpikePerformance tuningSQL optimization
0 likes · 12 min read
How to Diagnose and Resolve Online Slow SQL That Causes CPU Spikes
Architecture & Thinking
Architecture & Thinking
May 12, 2026 · Databases

Detecting and Solving Redis Hot Keys in Ten‑Million‑QPS Systems – A Complete Guide

The article analyzes how hot keys in Redis cause node overload, cache breakdown, and system avalanches in ten‑million‑QPS distributed systems, outlines four detection techniques, compares their trade‑offs, and presents five practical mitigation strategies with Go code examples and real‑world performance results.

CachingDistributed SystemsGo
0 likes · 33 min read
Detecting and Solving Redis Hot Keys in Ten‑Million‑QPS Systems – A Complete Guide
Java Architect Essentials
Java Architect Essentials
May 11, 2026 · Databases

Why SQLark Beats Navicat: An AI‑Powered Database Tool Review

The author compares common database clients, highlights the risks of cracked Navicat and limited DBeaver, then details how SQLark’s cross‑platform support, AI‑driven features, smart SQL editor, data migration, ER diagram generation, and test‑data generator provide a more efficient and secure workflow for developers.

AI assistantData MigrationDatabase Management
0 likes · 7 min read
Why SQLark Beats Navicat: An AI‑Powered Database Tool Review
dbaplus Community
dbaplus Community
May 11, 2026 · Databases

Why an Unindexed UPDATE Can Crash Your Business—and How to Prevent It

The article explains how running an UPDATE without an indexed WHERE clause in InnoDB under repeatable‑read can trigger full‑table next‑key locks that block other statements, halt the service, and how using indexed predicates, checking execution plans, enabling sql_safe_updates, or forcing an index can avoid the disaster.

InnoDBUPDATEindex
0 likes · 8 min read
Why an Unindexed UPDATE Can Crash Your Business—and How to Prevent It
ITPUB
ITPUB
May 11, 2026 · Databases

What Human Evolution Teaches About IT Architecture Trade‑offs (Ahead of the 2026 SACC)

The article draws a detailed analogy between millions of years of human evolution—standing up, shedding hair, expanding the brain, and recruiting ancient bacteria—and modern IT architecture, showing how each design choice brings hidden costs, why perfect systems are impossible, and how embracing trade‑offs, extensions, and continuous iteration can lead to resilient, self‑healing databases.

Cloud Nativearchitecturedatabases
0 likes · 22 min read
What Human Evolution Teaches About IT Architecture Trade‑offs (Ahead of the 2026 SACC)
Mingyi World Elasticsearch
Mingyi World Elasticsearch
May 11, 2026 · Databases

When Search Meets Rust: A Deep Dive into INFINI Pizza, the Next‑Gen Real‑Time Search Engine

This article analytically examines INFINI Pizza, a Rust‑implemented distributed search database, detailing its design philosophy, hierarchical data model, rolling‑partition‑shard architecture, share‑nothing + io_uring I/O stack, true real‑time indexing, in‑place partial updates, AI‑native hybrid search capabilities, ecosystem components, and a point‑by‑point comparison with Elasticsearch.

AI-nativeDistributedParquet
0 likes · 20 min read
When Search Meets Rust: A Deep Dive into INFINI Pizza, the Next‑Gen Real‑Time Search Engine
Java Tech Enthusiast
Java Tech Enthusiast
May 10, 2026 · Databases

Why Can Redis Handle Over 100k QPS? A Deep Technical Breakdown

Redis can sustain over 100,000 queries per second thanks to four key factors: pure in‑memory storage, highly optimized data structures such as SDS and ziplist, a single‑threaded event loop with epoll‑based I/O multiplexing, and optional multi‑threaded network handling introduced in Redis 6.0.

Data StructuresIO MultiplexingIn-Memory Database
0 likes · 10 min read
Why Can Redis Handle Over 100k QPS? A Deep Technical Breakdown
Su San Talks Tech
Su San Talks Tech
May 9, 2026 · Databases

Why Can Redis Handle Over 100,000 QPS? A Deep Technical Breakdown

Redis can sustain over 100,000 queries per second thanks to four key pillars—memory‑first storage, highly optimized data structures like SDS and skip lists, a single‑threaded event loop with epoll multiplexing, and multi‑core I/O threading—each explained with benchmarks, code samples, and real‑world comparisons.

Data StructuresIO MultiplexingPerformance
0 likes · 10 min read
Why Can Redis Handle Over 100,000 QPS? A Deep Technical Breakdown