New in v1.9 — CREATE AGENT · durable in-database agents
CREATE AGENT —
live in minutes.
Durable AI agents that fire on a schedule and on data changes, remember across restarts, and log every action to a tamper-evident audit trail — all declared with CREATE AGENT.
One binary. No GPU. Running in 5 minutes.
Fork the reference agent on GitHub·github.com/SynapCores/synapcores-agent
-- A durable agent, declared in SQL.
CREATE AGENT incident_triage
PERSONA 'aidb-assistant'
TASK 'Triage it: classify, name the attack
pattern, recommend an escalation tier.'
ON INSERT INTO incidents WHERE severity = 'critical'
WITH (max_iterations = 3, allow_writes = FALSE,
budget_tokens_per_day = 200000);
-- INSERT a critical row → the agent wakes
-- and acts, off the write path. Every run
-- lands in the immutable audit log.The agent lives in the database. No orchestrator, no queue, no worker fleet to run.
Reference agent on GitHub·Self-hosted — your data never leaves your box·No lock-in — single binary·Become a design partner and shape the roadmap →
The problem
Agents are easy to demo. Hard to actually run.
To put one real agent into production you assemble a stack — a framework, a queue, a worker fleet, a separate vector store, and an audit tool bolted on after. Five systems to run, secure, and keep in sync. Your data leaves the box. And when the agent acts, nothing is provable.
The stack you operate
Agent framework
LangGraph / CrewAI
Queue
Temporal / Celery
Worker fleet
always-on, scaled, paged
Vector store
a second database
Audit tooling
bolted on after
Five things to run, secure, and page someone about at 3am.
What SynapCores runs
The database.
One self-hosted binary. The agent, its memory, its schedule, and its audit trail all live inside it.
The shift
The database is the agent runtime.
The one sentence a bolt-on stack can't repeat
SynapCores is the only self-hosted, single-binary, no-GPU database where durable AI agents live inside the engine — declared with CREATE AGENT, fired by schedule and data changes, with memory, governance, and an immutable audit trail built in.
PROOF 01
Native schema-object agents
Agents are DDL objects that fire on INSERT / UPDATE / DELETE and on a schedule. No orchestrator, queue, or worker fleet to run or secure.
PROOF 02
Immutable audit, built in
Every agent action lands in a tamper-evident ledger — because the runtime is the system of record. Provable compliance, not a bolted-on log.
PROOF 03
One binary. No GPU. Your box.
Native in-process inference means the whole agentic stack runs on a cheap VPS with no model server — and your data never leaves.
See it fire
INSERT a row. Watch the agent act.
Three statements, one engine. No service to deploy, no queue to drain, no worker to page.
The same loop, recorded live against the engine — no mockups.
One query. Three systems other databases need.
SynapCores unifies graph traversal, vector similarity, and LLM inference into a single execution engine.
Graph traversal, HNSW vector similarity, and in-database ML aren't three services here — they're one execution engine. Each answers in a single statement, from microseconds for graph to a couple of milliseconds with embedding or model inference in the loop.
On Postgres that's pgvector + Apache AGE + a model server + your application code stitching them together. On SynapCores it's one query — and you can compose all three in a single MATCH.
Stack Comparison
| Stack | Systems | Round-trips |
|---|---|---|
| Pinecone + Postgres + OpenAI rerank | 3 + your service | 4–5 |
| Neo4j + external embedding + LLM | 3 + your service | 3–4 |
| SynapCores | 1 | 1 |
Start from a working recipe, not a blank file.
Every recipe is a self-contained markdown file with embedded SQL or Cypher. Run it locally, edit it, ship it. Here are three for agent memory — there are 187 more across graph, ML, and healthcare.
Store and recall memories by meaning with vector embeddings in plain SQL. Works with Claude Code, OpenClaw, LangChain, or any custom agent.
Blend semantic relevance with recency so the agent surfaces the right memory now, not a stale one — one SQL query, no extra cache layer.
Two memory types — episodic (what happened) and semantic (durable facts) — in one SQL store. Automatically promotes repeated episodes to facts.
Build agent memory in 5 emails.
One runnable SQL recipe per email. No LangChain. Free.
5-email course · free
Ship an agent with persistent memory in 5 emails
A 5-email course where you build a real agent with persistent memory — one runnable SQL recipe per email, no LangChain, no Pinecone, no Redis. Lesson 1 hits your inbox the second you sign up. After that: a new recipe every Monday. No spam.
Free forever. We'll never share your email.
What's in Community Edition
Community Edition is a complete AI-native engine. Sales is an upgrade path, not a front door.
| Feature | Community | Enterprise |
|---|---|---|
| Core SQL Engine | ||
| Vector Search (HNSW) | ||
| Graph Database (Cypher) | ||
| AI / LLM Integration | ||
| MCP Server (Model Context Protocol) | ||
| Multimedia (PDF/AV) | ||
| AutoML | ||
| Multi-node Clustering | ||
| Raft Replication | ||
| Fine-grained RBAC | ||
| Audit Logging (Scale) | ||
| SSO / SAML / LDAP | ||
| Immutable Tables |
Where we're going: v1.6 (Q3 2026) targets binary wire protocol, shared buffer pool, and B-tree indexes for OLTP at PG scale.
Building production agents? Partner with us early.
We're taking on a small number of design partners shaping the SynapCores roadmap. You get direct access to the engineering team, priority on the features you need, and SLA-backed support. We get a real workload to build against.
Become a design partner →Need clustering, RBAC, or production support?
The Enterprise Edition (EE) ships everything in CE plus mission-critical scale and security. Paid Enterprise Support is also available for CE deployments.
Scale
Multi-node clustering + Raft replication + CDC inbound from MySQL/Postgres binlog.
Security & Compliance
Fine-grained RBAC, SSO/SAML, LDAP, encryption-at-rest, audit logging, and immutable tables.
Performance
Binary wire protocol, shared buffer pool, row-store fast path (v1.6+).
Enterprise Support (also available for CE)
SLA-backed support for production CE deployments: prioritized bug fixes, custom feature work, roadmap input, and direct access to the engineering team. Buy support without buying EE.
Or start free with Community Edition