ClickHouse vs Supabase

Introducing ClickHouse's new TimeSeries Engine: Your drop-In Prometheus replacement

ClickHouse PromQL support lets you store Prometheus metrics in ClickHouse Cloud, query them using familiar PromQL, and bring metrics together with your logs and traces without rewriting queries in SQL.

High-Performance ETL for Apple Health XML Exports

This technical tutorial describes building a high-concurrency ETL engine to process very large Apple Health XML exports. The author outlines a performance-first architecture: a streaming Rust XML parser (quick-xml) to extract <Record> tags, export data as Apache Arrow record batches via PyO3 for zero-copy consumption in Python/Polars, and bulk-ingest cleaned data into ClickHouse using clickhouse-connect. The post includes code snippets for the Rust parser, Arrow-to-Polars bridge, ClickHouse table schema and bulk insert, and discusses production considerations such as parallelization, schema evolution, malformed XML handling, Grafana visualization, and feeding Arrow buffers into ML frameworks like PyTorch.

• Apple Health exports a single massive XML file containing millions of <Record> tags.
• The pipeline uses a streaming Rust parser (quick-xml) to avoid loading the entire XML into memory.
• Rust code is wrapped with PyO3 to return Apache Arrow tables for zero-copy consumption by Python/Polars.

NeverBlink Adds ClickHouse Support

NeverBlink, an AI-driven database administrator, announced support for ClickHouse, extending its database resilience and optimization platform to ClickHouse clusters. The integration offers continuous health checks, automated root-cause analysis, query analytics, prioritized remediation guidance, and optional unlimited expert consulting via BigData Boutique. NeverBlink already supports Elasticsearch and OpenSearch and is used in production by companies including Akamai, Perforce, and Palo Alto Networks. The article notes ClickHouse has surpassed 4,000 customers and a reported $15 billion valuation. Leadership quotes emphasize reducing downtime, lowering costs, and accelerating database optimization in the AI era.

• NeverBlink announced support for ClickHouse, extending its AI-native database resilience and optimization platform to ClickHouse clusters.
• NeverBlink is described as the world’s first AI database administrator (DBA) and already supports Elasticsearch and OpenSearch.
• ClickHouse has reportedly surpassed 4,000 customers and a reported $15 billion valuation.

Supabase is now available in Gemini Enterprise

Connect Supabase to Gemini Enterprise and query your Supabase projects with natural language, right inside the platform.

Build SaaS Apps with Claude Code, Clerk, and Supabase

This technical walkthrough guides product managers on how to build, secure, and monetize a full-stack B2B2C SaaS application using AI agents without writing code. Using a case study called AskOne—a live Q&A alternative to Slido—the tutorial details a universal, multi-step workflow. The process utilizes Anthropic's Claude Code to generate design layouts, establish design system tokens, and implement functional React components. The system integrates Clerk for user authentication and recurring subscription billing configuration, alongside Supabase as the backend database connected securely via Claude's Model Context Protocol (MCP) server framework.

• The author developed Grok Build for VS Code, achieving over 105,000 installations and 37,000 monthly active users (MAU).
• AI agents autonomously wrote 5,094 automated end-to-end integration and unit tests for the software in three months.
• The workflow utilizes a recommended B2B stack consisting of Next.js, Clerk, and Supabase.

Safely Drop All PostgreSQL Tables (2026)

A technical how-to describing safe methods to drop all tables in a PostgreSQL database. The article shows a one-command reset (DROP SCHEMA public CASCADE; CREATE SCHEMA public; GRANT ...), explains PostgreSQL 15 default changes that revoke CREATE from PUBLIC and set public's owner to pg_database_owner (which can cause permission errors), and details Supabase-specific risks (Dropping public can remove Supabase-managed schemas and extensions). It gives variants to preserve extensions (reinstall extensions or drop tables only via a DO-block loop), recommends wrapping resets in transactions for local dev, and provides a production safety checklist: take backups, confirm connection, block connections, and restore from pg_dump/pg_restore rather than dropping schema in prod.

• DROP SCHEMA public CASCADE removes the public schema and all dependent objects (tables, views, sequences, functions, triggers).
• PostgreSQL 15 defaults: PUBLIC no longer has CREATE by default, and the owner of public is pg_database_owner, which can cause 'permission denied for schema public' after recreating the schema.
• On Supabase, DROP SCHEMA public CASCADE can cascade into Supabase-managed schemas (auth, storage, realtime, graphql) and break the project; use 'supabase db reset' for dev and restore from backups for production.