PostgreSQL

An agentic PostgreSQL investigation is an AI-driven workflow that explores a database to answer operational questions, and OpsGraph makes it evidence-first: it discovers an approved read-only schema, validates every SELECT against the PostgreSQL AST and policy bounds, and records a tamper-evident audit chain so no conclusion can be asserted without opening its exact evidence. Instead of giving a model direct credentials and “asking it anything,” OpsGraph constrains the investigation to bounded, read-only, auditable queries that fail closed on unsafe SQL. ...

pg_clickhouse v0.10, released August 11, 2026, finally pushes correlated subqueries (SubPlans) down into ClickHouse, moving the TPC-H scoreboard from 12 to 16 of 22 queries fully pushed down. The headline result is TPC-H Q17, which dropped from 32.7 seconds to 37 milliseconds — roughly 880x faster and beating native PostgreSQL’s 2.1 seconds. This guide explains how subquery pushdown works, how to verify it with EXPLAIN, and what you need to upgrade to take advantage of it. ...

Every new RAG project I see starts the same way: spin up a Pinecone index, configure a Weaviate cluster, or deploy a Qdrant instance. It’s become the default move — like reaching for React before considering vanilla HTML. But after building and maintaining several production RAG systems over the last two years, I’ve found that vector databases are often the wrong first choice. The benchmark data backs this up. On the SQuAD dataset, BM25 keyword search achieves 88% recall@10 against 91.7% for OpenAI embeddings — a 3.7% gap that disappears in practice once you add reranking. Meanwhile, that vector database is eating 40-50% of your monthly RAG bill. If you’re running 50 queries per day in production, that’s roughly $1,000-$1,200/month just for the vector infrastructure. ...