RAG Explained Simply: How Retrieval-Augmented Generation Really Works
A plain-language guide to RAG, why it matters, where vector search fits, and how to think about retrieval quality before building an AI assistant.
DBApreneur is my working notebook for Oracle Database, Exadata, GoldenGate, Cassandra, MongoDB, PostgreSQL, automation, and AI-assisted database operations.
Step-by-step tutorials and practical scripts, organized by database technology.
26ai, architecture, space management, users, networking, patching, upgrades, and DBA fundamentals.
02AWR, ASH, Exadata, ADB, daily DBA checks, monitoring, and incident-response scripts.
03Setup, migration, resync, monitoring, patching, and troubleshooting notes.
04Cassandra, MongoDB, Couchbase, PostgreSQL, Presto, GoldenGate, and mixed database operations.
Database engineering is the core. I also write about AI, product thinking, automation, and the entrepreneurship path around DBA platforms.
LLMs, RAG, agents, and AI shipped to production.
SQL Server, Postgres, Oracle, Cassandra, Mongo, Yugabyte — replication, performance, and surviving 3am pages.
Discovery, prioritization, and shipping what people use.
Bootstrapping, niches, pricing, and the real reality.
Practical DBA notes, architecture write-ups, scripts, and field lessons.
A plain-language guide to RAG, why it matters, where vector search fits, and how to think about retrieval quality before building an AI assistant.
A practical look at AI agents for DBA work: monitoring, runbooks, SQL explanation, incident triage, and the guardrails needed before automation.
A DBA-friendly introduction to Oracle tablespaces, data files, autoextend, free space, temp usage, undo, and the SQL checks every Oracle admin should know.