# Glean vs Polygres

Glean records 3,301,875 monthly visits with +0.1% month-over-month growth and Contact for Pricing pricing. Polygres records 4,018 monthly visits with -52.3% growth and Freemium pricing.

| Metric | [Glean](https://openaitools.app/tool/glean) | [Polygres](https://openaitools.app/tool/polygres) |
| :--- | :--- | :--- |
| Website URL | https://www.glean.com | https://polygres.com |
| Categories | AI Productivity Tools, AI Agent, AI Assistant, AI Search Engine | AI Developer Tools, AI Agent, AI Knowledge Graph, AI API |
| Pricing Model | Contact for Pricing | Freemium |
| Monthly Visits | 3,301,875 | 4,018 |
| MoM Growth Rate | +0.1% | -52.3% |
| Primary Market | United States | Global |
| Direct Visits | 2,628,666 | 1,605 |
| Review Score | 4.6 | 4.1 |
| Saved Count | 7 | 0 |
| Supported Platforms | Website | Website |

## Glean

Glean addresses a problem most enterprises hit after their first wave of AI adoption: models are powerful but isolated from the context of the business. The platform builds an enterprise context layer by indexing and understanding content across the tools a company already runs on, then uses that grounding to improve both answer quality and efficiency. Because fewer irrelevant tokens need to be sent to a model, the same question costs less to serve.

The product surface spans four areas: enterprise search, an AI assistant for everyday work, an agent platform for automating long-running processes, and Glean Protect for security and governance. Administrators also get model routing and an AI gateway, letting them decide which models handle which requests without rebuilding integrations. Everything inherits the access permissions of the source systems, so answers stay within each employee's existing rights.

Glean serves large organisations across finance, healthcare, retail, technology, and government, with published customers including Booking.com, Zillow, and Ericsson. It holds SOC 2 Type II, ISO 27001, ISO 42001, HIPAA, GDPR, and TX-RAMP Level 2 attestations, and reports 275+ connectors, 40+ supported language models, and 99.9%+ uptime on core services.

**Pricing & Plans:** Contact for pricing. Glean is licensed to organisations based on seats, connectors, and deployment scope, and is evaluated through a demo rather than self-serve purchase.

- **Permission-aware enterprise search:** Ask a question in plain language and get a cited answer assembled from documents, tickets, wikis, and messages across every connected system, with permissions respected.
- **Agent builder and orchestration:** Reusable agents handle multi-step workflows such as onboarding, account research, or incident follow-up by orchestrating actions across business apps.
- **Model routing and AI gateway:** Glean automatically picks and routes requests to the right model and reasoning level, giving teams access to 40+ LLMs through a single governed gateway.
- **Grounded content and analysis:** Draft on-brand documents, summarise meetings, analyse data, and create content grounded in company context rather than generic model knowledge.
- **Governance and observability:** Administrators get usage controls, spend visibility, audit logging, and compliance-ready governance for every AI interaction.

**Strengths:** Answers cite source systems and inherit their permissions, which removes the main blocker to enterprise-wide rollout; One platform covers search, assistant, and agents instead of three separate vendors; Model routing and token efficiency directly reduce the cost per AI query at scale; 275+ pre-built connectors shorten integration work considerably

**Limitations:** Enterprise pricing is quote-based, so budget planning requires a sales conversation; Full value depends on connecting many internal data sources, which takes IT effort; Smallest teams may find the platform more than they need

[Profile (Markdown)](https://openaitools.app/tool/glean.md)

## Polygres

Polygres is a retrieval platform that treats PostgreSQL as the backbone for AI-native applications. Rather than forcing teams to migrate to a new vector-only database, it virtualises a GraphRAG-style retrieval layer on top of Postgres, so existing relational records, embeddings and text indexes stay where they are while agents gain the ability to search by meaning, follow relationships and match exact wording in one request.

The platform bundles four complementary retrieval modes: semantic vector search for meaning, graph traversal for multi-hop relationships and shortest-path style queries, full-text search for exact terms, and hybrid search that blends them. Developers reach these capabilities through a hosted playground, a CLI for managing projects and imports, and a typed Python SDK for production applications.

Behind the managed platform are two open-source engines, pgGraph for graph traversal inside Postgres and pgContext for AI search, which teams can inspect, benchmark and self-host. Polygres supports both a managed database hosted by the company and connecting an existing Postgres instance, and it markets itself around agent memory, grounded answers with sources, product semantic search and recommendation systems.

**Pricing & Plans:** Polygres follows a freemium model with a free tier for getting started and paid managed plans for production workloads. Exact tiers are published on the company's pricing page, so check there for current numbers before budgeting.

- **Unified retrieval API:** Query graph, vector, full-text and hybrid retrieval through one consistent interface instead of stitching multiple systems together.
- **Graph traversal on Postgres:** The open-source pgGraph engine follows relationships across your records, enabling multi-hop and shortest-path retrieval without moving data.
- **Vector and hybrid search:** Semantic search over embeddings combines with sparse and full-text matching so queries that mix meaning and exact terms still work.
- **Developer toolkit:** A dashboard playground, CLI for imports and configuration, and a typed Python SDK make it straightforward to prototype and then ship.
- **Managed or bring-your-own Postgres:** Start on a Polygres-hosted database or connect an existing Postgres instance and extend what you already run.

**Strengths:** Keeps your existing PostgreSQL instead of forcing a migration to a specialised vector store; Combines four retrieval modes in one platform, which reduces the number of moving parts in a RAG stack; Core engines pgGraph and pgContext are open source, so the internals are inspectable and self-hostable; Familiar Postgres tooling, SQL knowledge and connection patterns carry over for most teams

**Limitations:** Team and community are relatively early-stage, so long-term support and ecosystem maturity are still developing; Being a newer product, third-party tutorials and integrations are thinner than for established vector databases; Fully managed convenience depends on using the hosted offering rather than the open-source engines alone

[Profile (Markdown)](https://openaitools.app/tool/polygres.md)

## Frequently Asked Questions

### How do Glean and Polygres compare in monthly traffic?

Glean has 3,301,875 monthly visits, while Polygres has 4,018. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Glean has a month-over-month growth rate of +0.1%; Polygres has -52.3%.

### How does pricing compare?

Glean: Contact for Pricing. Contact for pricing. Glean is licensed to organisations based on seats, connectors, and deployment scope, and is evaluated through a demo rather than self-serve purchase. Polygres: Freemium. Polygres follows a freemium model with a free tier for getting started and paid managed plans for production workloads. Exact tiers are published on the company's pricing page, so check there for current numbers before budgeting.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Notion](https://openaitools.app/tool/t) | 173,441,670 | +0.1% | Freemium | The AI workspace where teams and agents get work done together | [.md](https://openaitools.app/tool/t.md) |
| 2 | [Exa](https://openaitools.app/tool/exa-ai) | 1,062,574 | +16.8% | Freemium, Contact for Pricing | Web search API and crawler built for AI agents | [.md](https://openaitools.app/tool/exa-ai.md) |
| 3 | [You.com](https://openaitools.app/tool/you) | 948,349 | +7% | Freemium | Search and inference APIs that give AI models real-time web data | [.md](https://openaitools.app/tool/you.md) |
| 4 | [Algolia](https://openaitools.app/tool/algolia) | 689,970 | -11% | Freemium, Contact for Pricing | AI search and retrieval platform for modern apps and commerce | [.md](https://openaitools.app/tool/algolia.md) |
| 5 | [Dust](https://openaitools.app/tool/dust) | 547,217 | +1.8% | Contact for Pricing | Builds collaborative enterprise AI agents connected to company knowledge, but offers less robust out-of-the-box universal search. | [.md](https://openaitools.app/tool/dust.md) |
| 6 | [Gumloop](https://openaitools.app/tool/gumloop) | 379,557 | -21.1% | Freemium, Paid, Contact for Pricing | Build, share, and control AI agents that actually do the work | [.md](https://openaitools.app/tool/gumloop.md) |
| 7 | [Pinecone](https://openaitools.app/tool/pinecone) | 286,732 | -31% | Freemium, Paid, Contact for Pricing | The managed vector database and knowledge engine for production AI | [.md](https://openaitools.app/tool/pinecone.md) |
| 8 | [Moveworks](https://openaitools.app/tool/moveworks) | 168,527 | -4.3% | Contact for Pricing | Automates employee IT and HR support requests exceptionally well, but focuses less on general universal document search. | [.md](https://openaitools.app/tool/moveworks.md) |
| 9 | [supermemory](https://openaitools.app/tool/supermemory-1) | 156,579 | -7.7% | Contact for Pricing | A memory and continual-learning engine that gives any AI agent persistent context | [.md](https://openaitools.app/tool/supermemory-1.md) |
| 10 | [Yep.com](https://openaitools.app/tool/yep-com) | 155,834 | +6.2% | Free | Independent web search and agent grounding API built on the Ahrefs index | [.md](https://openaitools.app/tool/yep-com.md) |

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Source: https://openaitools.app/compare/glean-vs-polygres

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