PgGraph
Virtual graph layer for Postgres — query relationships in milliseconds, no data moved.
PgGraph is a pragmatic, Rust-powered graph layer for Postgres that avoids data duplication. Ideal for latency-sensitive AI agents, but not a full graph DB replacement. Best for developers already on Postgres who need fast multi-hop queries without adding a second database. For teams needing a managed solution, consider the separate Polygres cloud offering. If you require a full graph database with its own storage engine, Neo4j or Amazon Neptune may be more appropriate.
- Developers building AI agents on Postgres
- Teams needing graph queries without a second database
- Fintech and marketplace platforms for fraud detection
- SaaS teams with complex permission models
- Users looking for a traditional graph database with its own storage engine
- Teams that cannot self-host or manage a Rust service
- Those needing graph visualization or UI tools out of the box
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Skip PgGraph if you need a full graph database with its own storage engine, or if you cannot self-host a Rust service.
Self-hosting requires operational overhead for managing a Rust service in production.
PgGraph is free and open-source, making it cost-effective for startups and small teams already on Postgres. For self-hosted graph capabilities, it's cheaper than running a separate Neo4j instance. Managed alternatives like Neo4j Aura or Amazon Neptune cost significantly more for similar throughput, but they offer zero operational overhead.
In short
PgGraph — Virtual graph layer for Postgres — query relationships in milliseconds, no data moved. Best for Developers building AI agents on Postgres, Teams needing graph queries without a second database, Fintech and marketplace platforms for fraud detection. Free to use.
What's new in PgGraph
Checked 11 days agoAcross the latest 3 updates: 3 news mentions.
Postgres as a Graph Database: Four Approaches Compared
Compares recursive CTEs, pgRouting, Apache AGE, and PgGraph for graph queries on Postgres.
Buying pggraph.com: A Domain Meant to Be
Evokoa bought the pggraph.com domain for $10 from a squatter who had it for years.
Lessons from John Carmack: Why We Built pgGraph Like a Game Engine
Explains how game engine memory layout and hot-loop principles influenced PgGraph's Rust architecture.
Viability Score
How likely is PgGraph to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- Virtual graph layer over Postgres
- No data movement or duplication
- Multi-hop relationship traversal in milliseconds
- Rust-based engine for low latency and concurrency
- Live hydration from Postgres source of truth
- Lightweight relationship index (memory efficient)
- Agentic memory for AI agents
- Real-time fraud detection and permission checks
- Dependency and blast radius analysis
- Supports existing Postgres schemas without migration
- Open source with API for integration
- 34x less RAM than traditional graph databases
- Concurrent read/write safe
About PgGraph
PgGraph is an open-source graph traversal engine built by Evokoa that sits atop your existing PostgreSQL database. It creates a lightweight in-memory index of relationships (IDs, foreign keys) without copying the underlying row data. When an application or AI agent queries for connected records, PgGraph traverses the relationship map, identifies the relevant rows, and fetches them live from Postgres. This approach avoids the overhead of a second graph database while enabling sub-millisecond multi-hop queries. The tool is designed for teams building AI agents, internal tools, fraud detection, permission checks, and dependency analysis — any scenario where entities are implicitly connected via foreign keys but need to be queried as a graph. It is particularly suited for developers who already rely on Postgres and want to add graph capabilities without ETL, schema migration, or data duplication. What distinguishes PgGraph is its architecture: written in Rust for low-latency and concurrent access, it uses ~34x less RAM than traditional graph databases (based on the Panama Papers dataset benchmark). It maintains Postgres as the single source of truth, eliminating sync issues. The engine exposes a single API to traverse relationships, making it compatible with any language or framework that can make HTTP requests. PgGraph is fully open-source (source code available on GitHub). Core features like the relationship index and traversal API are free. There is a managed cloud version (Polygres) recently announced for the agent era, but the open-source project remains the primary focus for self-hosted deployments.
Behind the Verdict
PgGraph fills a real gap: Postgres holds relational data, but querying multi-hop paths via recursive CTEs is slow and painful. PgGraph's approach of keeping a lightweight in-memory index of foreign keys and fetching rows live is clever and efficient. The Rust-based engine delivers low and predictable latency, which is critical for AI agent workflows that need to retrieve context across several linked records in real-time. The open-source nature means you can inspect and customize the code, and there's no vendor lock-in. The memory efficiency (34x less RAM than traditional graph databases on the Panama Papers dataset) is a strong selling point for cost-conscious teams. However, PgGraph is not a graph database — it doesn't store data, and it requires your Postgres instance to be online and responsive. It also assumes your relationships are expressed as foreign keys; arbitrary property graph models (like those with inline properties on edges) are not supported out of the box. The open-source version is self-hosted, so you'll need to manage a Rust service on your infrastructure. For teams that want a managed experience, Evokoa has launched Polygres, a cloud version for the agent era. But PgGraph itself remains a solid self-hosted option for those who value keeping Postgres as the single source of truth.
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Real-world workflow fit
Concrete scenarios for the personas PgGraph actually fits — and what changes day-one when you adopt it.
Build a customer support bot that needs to pull a user's full context — tickets, invoices, contracts, and SLA history — from Postgres tables linked by foreign keys.
Outcome: PgGraph indexes the relationships once, then the bot queries multi-hop paths via the API in milliseconds, returning a hydrated response with all relevant records.
Detect fraud rings by checking if a new account shares device IDs, IPs, or merchant accounts with known bad actors.
Outcome: PgGraph traverses 3-4 hops from the new account to suspicious entities in under a second, flagging the transaction for review.
Perform impact analysis to see which services, teams, or customers would be affected if a specific database record is deleted.
Outcome: PgGraph returns a list of dependent records across tables, allowing the engineer to assess blast radius before making changes.
Use Cases
- Enable AI agents to traverse customer-to-contract-to-SLA relationships in milliseconds.
- Detect fraud rings by querying multi-hop connections between devices, accounts, and merchants in real time.
- Build support copilots that pull the full customer context across tickets, invoices, and approvals instantly.
- Enforce permission checks by resolving role-resource-workspace chains without denormalization.
- Perform impact analysis to see what breaks if a service, supplier, or record changes.
Limitations
- PgGraph is an index layer and does not store data; it requires the original Postgres database to be online.
- It is designed for SQL-based relationships (foreign keys) and may not support arbitrary property graph models.
- The open-source version is self-hosted, so users must manage their own infrastructure.
- No rate limits or plan gating currently documented.
as of 2026-07-06
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published PgGraph tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Open Source (Community)
$0
Ideal for
Developers and small teams who can self-host and want full control over their graph layer without per-seat costs.
What this tier adds
Free entry point: all core features (index, traversal API, live hydration) are included with no usage caps.
Where the pricing makes sense
The company stage and team size where PgGraph's pricing actually pencils out — and where peers do it cheaper.
PgGraph is free and open-source, making it cost-effective for startups and small teams already on Postgres. For self-hosted graph capabilities, it's cheaper than running a separate Neo4j instance. Managed alternatives like Neo4j Aura or Amazon Neptune cost significantly more for similar throughput, but they offer zero operational overhead.
Setup time & first value
How long it actually takes to get something useful out of PgGraph — broken out by persona, not the marketing-page minute.
For developers already using Postgres: install the Rust binary, configure the database connection, and run the indexer. Expect first traversal results within 10-30 minutes, including schema introspection and indexing of foreign keys.
Switching to or from PgGraph
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Recursive CTEs: Replace slow recursive queries with a single PgGraph API call to traverse the same paths instantly.
- →From Neo4j: Export your data model as SQL relations into Postgres, then let PgGraph index foreign keys — no ETL pipeline needed.
- ↗To Neo4j: Export Postgres data as CSV and import into Neo4j using Cypher LOAD CSV, but you lose live hydration.
- ↗To Polygres: Migrate your PgGraph instance to Polygres for a managed cloud experience — same API, zero code changes.
Integrations
Resources & Guides
Official links
Tools that pair well with PgGraph
Common stack mates teams adopt alongside PgGraph, with the specific reason each pairing earns its keep.
Featured Head-to-Head Comparisons
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Best-of guides
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