Tags: Database

Boring technology won the wildest era. A look at extensibility, agent choice, database cloning, and the future of the DBA.

Should we still hire fresh grads? Squeezed between AI and senior devs, what's the play for new programmers? Master the right tools, take initiative, find the right mentor.

A conversation between Mike Stonebraker (Turing Award Winner, Creator of PostgreSQL), Andy Pavlo (Carnegie Mellon), and the DBOS team.

The bottleneck for AI agents isn't in database engines but in upper-layer integration. Muscle memory, associative memory, and trial-and-error courage will be key.

MySQL is to the internet what baijiu is to China: harsh, hard to swallow, yet worshipped because culture demands obedience. Both are loyalty tests—will you endure discomfort to fit in?

MinIO just entered maintenance mode. What replaces it? Can RustFS step in? I tested the contenders so you don’t have to.

MinIO announces that it is entering maintenance mode: the dragon-slayer has become the dragon. This is how MinIO transformed from an open-source S3 alternative into just another commercial software company.

Context window economics, the polyglot persistence problem, and the triumph of zero-glue architecture make PostgreSQL the database king of the AI era.

The database world is full of hype and marketing fog. This column cuts through it with blunt commentary on industry trends and product reality.

Imagine a “closed-course” shootout for domestic databases and clouds, the way Dongchedi just humiliated 30+ autonomous cars. This industry needs its own stress test.

Google recently launched a database MCP toolbox, perhaps the first production-ready solution.

Who will be revolutionized first - OLTP or OLAP? Integration vs specialization, how to choose? Where will DBAs go in the AI era? Feng's views from the HOW 2025 conference roundtable, organized and published.

The database for the AI era has been settled. Capital markets are making intensive moves on PostgreSQL targets, with PG having become the default database for the AI era.

Three emerging standards in the data world: Postgres, OpenTelemetry, and Iceberg. Postgres is already the de facto standard.

If DuckDB had launched in 2012, the great migration to distributed analytics might never have happened. Data isn't that big after all.

Plenty. If you’re rolling your own Kubernetes, odds are you’ll crash because etcd ships with a 2 GB time bomb.

Future software = Agent + Database. No middle tiers, just agents issuing CRUD. Database skills age well, and PostgreSQL is poised to be the agent-era default.

A 2025 reality check on where PostgreSQL stands relative to MySQL across features, performance, quality, and ecosystem.

If you ask me, we’re on the brink of a cosmic collision in database-land, and Postgres + DuckDB is the meteor we should all be watching.

The PG community has started punching up: Cybertec’s Laurenz Albe breaks down how Oracle’s transaction system stacks against PostgreSQL.

An interesting but tricky puzzle: solving the 24 game with SQL. The PostgreSQL solution.

Is PostgreSQL the king of boring databases? Here are seven databases worth studying in 2025: PostgreSQL, SQLite, DuckDB, ClickHouse, FoundationDB, TigerBeetle, and CockroachDB—each deserving a week of deep exploration.

Supabase is an open-source PostgreSQL-based BaaS. It provides authentication, Realtime, Edge Functions, object storage, and REST APIs generated from the database schema; enabling pg_graphql on demand also provides GraphQL APIs. Self-hosting can make …

A survey on how hardware developments affect database design, covering key advancements in networking, storage, and computing.

Percona founder Peter Zaitsev discusses whether MySQL can still keep up with PostgreSQL. His views largely represent the MySQL communitys perspective.

Programmers are expensive, scarce biological computing cores, the anchor point of software costs — please prioritize optimizing biological cores before optimizing CPU cores.

MongoDB 3.2's analytics subsystem turned out to be an embedded PostgreSQL database? A whistleblowing story from MongoDB's partner about betrayal and disillusionment.

This July, MySQL 9.0 was finally released—a full eight years after its last major version, 8.0 (@2016-09).

Percona founder Peter Zaitsev publicly expressed disappointment with MySQL and Oracle, criticizing the declining performance with newer versions.

Peter Zaitsev, founder of Percona, criticizes how Oracles actions and inactions have killed MySQL. About 15 years after acquiring Sun and MySQL.

Higher MySQL versions mean worse performance? Percona monitoring shows slow migration from 5.7 to 8.x. PostgreSQL is pulling ahead.

Today we discuss the fair pricing of commercial databases, open-source databases, cloud databases, and domestic Chinese databases.

Friends often ask me, **can Chinese domestic databases really compete?** To be honest, **it's a question that offends people**. So let's try speaking with data - I hope the charts provided in this article can help readers understand the database ecosystem landscape and establish more accurate proportional awareness.

Redis "going non-open source" is not a disgrace to Redis, but a disgrace to "open source/OSI" and even more so to public cloud. What truly matters has always been software freedom, while open source is just one means to achieve software freedom.

MySQL's transaction ACID has flaws and doesn't match documentation promises. This may lead to serious correctness issues - use with caution.

Whether databases should be housed in Kubernetes/Docker remains highly controversial. While Kubernetes (k8s) excels in managing stateless applications, it has fundamental drawbacks with stateful services, especially databases like PostgreSQL and …

Whether databases should be housed in Kubernetes/Docker remains highly controversial. While K8s excels in managing stateless applications, it has fundamental drawbacks with stateful services like databases.

Vector storage and retrieval is a real need, but specialized vector databases are already dead. Small needs are solved by OpenAI directly, standard needs are captured by existing mature databases with vector extensions. The ecological niche left for specialized vector databases might support one company, but trying to build an industry around AI stories is impossible.

Many "domestic databases" are just shoddy, inferior products that can't be helped. Xinchuang domestic OS/databases are essentially **IT pre-made meals in schools**. Users hold their noses while migrating, developers pretend to work hard, and everyone plays along with leaders who neither understand nor care about technology. The infrastructure software industry isn't being strangled by anyone - the real chokehold comes from the so-called "insiders."

RHEL-series OS distribution compatibility level: RHEL = Rocky ≈ Anolis > Alma > Oracle >> Euler. Recommend using RockyLinux 8.8, or Anolis 8.8 for domestic requirements.

When we talk about self-reliance and control, what are we really talking about? Operational self-reliance vs. R&D self-reliance - what nations/users truly need is the former, not flashy "self-research".

The cost-cutting imperative has triggered a reevaluation of all technologies, including databases. This series critiques hot DB technologies and poses fundamental questions about their trade-offs: Are cloud databases, distributed databases, microservices, and containerization real needs or false hype?

Similar to Maslow's hierarchy of needs, user demands for databases also have a progressive hierarchy: physiological needs, safety needs, belonging needs, esteem needs, cognitive needs, aesthetic needs, self-actualization needs, and transcendence needs.

As hardware technology advances, the capacity and performance of standalone databases have reached unprecedented heights, which makes distributed (TP) databases appear utterly powerless, much like the "data middle platform" wearing the emperor's new clothes.

Thou shalt not run a prod database inside a container

A proper understanding of time is very helpful for correctly handling time-related issues in work and life. For example, time representation and processing in computers, as well as time handling in databases and programming languages.

Without understanding the basic principles of character encoding, even simple string operations like comparison, sorting, and random access can easily lead you into pitfalls. This article attempts to clarify these issues through a comprehensive explanation.

Concurrent programs are hard to write correctly and even harder to write well. Many programmers simply throw these problems at the database... But even the most sophisticated databases won't help if you don't understand concurrency anomalies and isolation levels.

The technical essence, functionality, and evolution of blockchain is distributed databases. Specifically, it's a **Byzantine Fault Tolerant (resistant to malicious node attacks) distributed (leaderless replication) database**.

The term "consistency" is heavily overloaded, representing different concepts in different contexts. For example, the C in ACID and the C in CAP actually refer to different concepts.

Those who only know how to code are just programmers; **learn databases well, and you can at least make a living**; but for **excellent** engineers, merely **using** databases is far from enough.