Show HN: DeepSQL – A self-hostable AI DBA agent for Postgres and MySQL
DeepSQL is a self-hostable AI DBA agent designed for Postgres and MySQL databases. It allows users to add database connections, teach it their company's knowledge, and feed it slow query logs to improve performance. DeepSQL indexes the schema and starts learning the workload immediately, providing recommendations for improvement.
- ▪DeepSQL supports both Postgres and MySQL databases, including read replicas and VPC-peered connections.
- ▪The agent learns the company's knowledge through plain English business rules, such as MRR and active hotel definitions.
- ▪DeepSQL analyzes slow query logs from pg_stat_statements or MySQL slow log, clustering and ranking queries to provide recommendations.
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | DeepSQL |
| Canonical URL | https://deepsql.ai/ |
| Publication time | Mon, 20 Jul 2026 15:32:20 +0000 |
| Retrieval time | 2026-07-20T15:53:38.925Z |
| Last seen | 2026-07-20T15:53:38.925Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | pGYQwdlLYUBH |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Add database connections, teach it your company's knowledge, and feed it your slow query logs. DeepSQL indexes your schema and starts learning your workload immediately.Database connectionsPostgres or MySQL — read replica, VPC-peered. Read-only credentials, no data leaves your infra.host: aws-rds-replica.internalrole: deepsql_rossl: requireCompany knowledgeTeach DeepSQL your business rules in plain English — MRR, active-hotel, currency conventions.// MRR = SUM(subscription.mrr)// WHERE status = 'active'// Active hotel = check-ins ≥ 1 / 30dSlow query logsPoint at pg_stat_statements or MySQL slow log. DeepSQL clusters, ranks, and starts recommending.source: pg_stat_statementswindow: 30d rollinggrouped: 1,284 → 96 fingerprints
Excerpt limited to ~120 words for fair-use compliance. The full article is at DeepSQL.
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