Show HN: SynapCores – AI-native database (vector, graph, SQL, AutoML, LLM)
SynapCores has launched an AI-native database that integrates graph traversal, vector similarity, and LLM inference into a single execution engine. The Community Edition is free and allows users to run AI-augmented queries in about 30 seconds. This database aims to simplify complex queries by unifying multiple workloads into one statement.
- ▪SynapCores combines graph traversal, vector similarity, and LLM inference into a single execution engine.
- ▪The Community Edition is free and production-ready, allowing users to execute AI-augmented queries quickly.
- ▪Users can access 148 ready-to-run recipes to experiment with various functionalities of the database.
Hacker News (Show HN) files mainly under programming. We currently carry 68 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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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 | SynapCores |
| Canonical URL | https://synapcores.com |
| Publication time | Mon, 25 May 2026 16:28:38 +0000 |
| Retrieval time | 2026-05-25T16:37:38.283Z |
| Last seen | 2026-05-25T16:37:38.283Z |
| 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 | 1Gj7g5bmq2tL |
| 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
New — Native MCP + OpenClaw long-term memoryGraph + Vector + LLM + MCP. One database. One query.Free, single-binary install. Production-ready Community Edition. ~30 seconds to your first AI-augmented query.$curl -fsSL https://get.synapcores.com | shWant to see it run first?Watch the 5 live demosPrefer a packaged installer?All download options★ 5 LIVE DEMOS★ 161 READY-TO-RUN RECIPES★ NATIVE MCP★ OPENCLAW MEMORY★ MACOS + LINUX + DOCKER★ OPEN COMMUNITY EDITIONOne query. Three systems other databases need.SynapCores unifies graph traversal, vector similarity, and LLM inference into a single execution engine.GraphVectorIn-DB MLsynapcores · cypherone engine> ▋Same engine, three workloads — graph, vectors, and ML — each in one statement.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at SynapCores.
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