Clickhouse on Lorbic

ClickHouse data masking with regex

Tue, 31 Mar 2026 22:30:00 +0530

If you’re running a production observability stack, you’ve already leaked PII. An engineer forgot to redact an email in a log line, or a JWT token ended up in a stack trace.

In most databases, the only fix is to DELETE the data—killing your metrics along with the sensitive info. But ClickHouse has a more elegant approach: Data Masking Policies.

By defining a policy at the role level, you can use regex to swap sensitive patterns with [REDACTED] in real-time, before the query results even leave the server.

ClickHouse vs. Postgres: When to Move Your Logs Out of a Relational DB

Mon, 30 Mar 2026 22:45:00 +0530

Postgres is the most reliable tool in my stack. It handles users, configurations, and complex relations without breaking a sweat. But databases, like any physical system, have a “design limit”. For Postgres, that limit usually appears when you try to use it as a dumping ground for high-velocity logs and metrics.

When your ANALYZE commands start taking minutes and your indexes consume more RAM than your data, you aren’t facing a Postgres bug; you’re facing an architectural mismatch.

Can ClickHouse Replace Vector Databases? HNSW, Benchmarks & SQL Setup

Wed, 14 Jan 2026 20:00:00 +0530

Everyone’s building AI apps now. And every AI app needs a place to stash embeddings. The instant your data grows beyond “fits in memory”, you need a vector database. Or do you?

If you’re already running ClickHouse for analytics, here’s some good news: you might not need another database. ClickHouse can hold its own as a vector store. Not because it was built for it, but because it’s built to be fast at everything.

OLTP vs OLAP - Why You Need Two Databases

Sun, 11 Jan 2026 21:00:00 +0530

At a recent ClickHouse conference in New Delhi, I attended this Saturday. There were many interesting sessions, but one that stood out was a talk on multi-tenant analytics at scale. I was reminded of a fundamental truth in backend engineering: “The database that runs your app cannot be the database that analyzes your app”.

Early in a startup’s life, we shove everything into one database. User profiles, session data, logs, and analytics events all live in the same Postgres, Mongo, or Couchbase instance. It works, until it throttles.