# Polygres vs Powabase

Polygres records 4,018 monthly visits with -52.3% month-over-month growth and Freemium pricing. Powabase records 0 monthly visits with -100% growth and Freemium pricing.

| Metric | [Polygres](https://openaitools.app/tool/polygres) | [Powabase](https://openaitools.app/tool/powabase) |
| :--- | :--- | :--- |
| Website URL | https://polygres.com | https://powabase.ai |
| Categories | AI Developer Tools, AI Agent, AI Knowledge Graph, AI API | AI Developer Tools, AI Agent, AI Knowledge Base, AI Workflow |
| Pricing Model | Freemium | Freemium |
| Monthly Visits | 4,018 | 0 |
| MoM Growth Rate | -52.3% | -100% |
| Primary Market | Global | Global |
| Direct Visits | 1,605 | 0 |
| Review Score | 4.1 | 4.6 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## 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)

## Powabase

Powabase starts from PostgreSQL and layers the pieces AI products need — retrieval, agents, and workflows — directly onto the database instead of forcing developers to glue together a vector store, an agent framework, and a BaaS. Every project receives its own isolated Postgres instance with row-level security, along with a first-class auth service, object storage, and realtime. Access happens through PostgREST, a REST/GraphQL-style API, or a direct database connection.

The RAG layer is a core feature, not a bolt-on. When you upload PDFs, images, office documents, or URLs, Powabase extracts, chunks, embeds, and indexes the content automatically, then serves it through BM25, pgvector, hybrid search, multimodal indexing, and rerankers. On top of that sits an agent runtime: you define ReAct orchestrations that combine multiple LLMs, knowledge bases, and tools, and it executes them over HTTP or MCP with streaming responses, persistent sessions stored in your project's Postgres, and human approval for sensitive calls. A visual workflow builder lets you assemble multi-step flows by dragging blocks, then publish them as HTTP endpoints.

Powabase also leans hard into AI-assisted development. It publishes an agent skill and an MCP server so coding tools such as Claude Code, Codex, Antigravity, OpenCode, Replit, Lovable, v0, Base44, and Bolt.new can speak the platform natively. Deployment is flexible: run it on Powabase Cloud, self-host the Apache-2.0 stack with a single docker compose up, or deploy on Kubernetes via the official Helm chart for enterprise use — always bringing your own LLM keys.

**Pricing & Plans:** Powabase follows an open-core model. The full stack is free and open source under Apache-2.0, so you can self-host with Docker Compose at no license cost. A fully managed Powabase Cloud handles updates, backups, and scaling, and an Enterprise edition adds a supported Kubernetes deployment with SLAs and private hosting. Public fixed price points are not listed on the homepage; contact the team for cloud and enterprise quotes.

- **Dedicated Postgres per project:** Every project runs its own isolated PostgreSQL instance with row-level security, plus managed auth, object storage, and realtime subscriptions — no shared logical databases and no noisy-neighbor risk.
- **Built-in RAG pipeline:** Upload PDFs, images, office files, or URLs and Powabase extracts, chunks, embeds, and indexes them automatically. It supports BM25, pgvector, hybrid search, multimodal indexing, and rerankers.
- **Agents with tools over HTTP or MCP:** Define ReAct-style agents with multiple LLMs, knowledge bases, and tools. Runs stream over SSE and sessions persist in your project's Postgres, with human approval gates for sensitive tool calls.
- **Visual, callable workflows:** Drag and connect blocks — triggers, conditions, agents, HTTP calls, code — to assemble multi-step workflows, or ask a natural-language copilot to draft the flow. Deploy a workflow as an HTTP endpoint.
- **Open source and self-hostable:** Clone the Apache-2.0 repo and run docker compose up for a single-project stack on your own infrastructure. A managed cloud and an enterprise Helm chart deployment are also available.

**Strengths:** Postgres-native architecture with a dedicated, isolated database per project rather than shared logical databases.; RAG, agents, workflows, auth, and storage bundled behind one REST API, cutting down on glue code.; RAG pipeline is production-oriented, with hybrid search, rerankers, OCR, and multimodal indexing included.; Fully open source under Apache-2.0, so self-hosting avoids vendor lock-in.

**Limitations:** The platform assumes you already know your way around Postgres; teams that just want a drag-and-drop database without SQL concepts may find the learning curve steeper than a fully no-code tool.; Self-hosting the full stack means running around a dozen Docker services on your own infrastructure, which carries real operational overhead.; You bring your own LLM API keys, so model spend and rate limits are managed outside Powabase.; The homepage does not publish fixed public prices, so budget planning for cloud or enterprise plans requires contacting sales.

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

## Frequently Asked Questions

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

Polygres has 4,018 monthly visits, while Powabase has 0. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Polygres has a month-over-month growth rate of -52.3%; Powabase has -100%.

### How does pricing compare?

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. Powabase: Freemium. Powabase follows an open-core model. The full stack is free and open source under Apache-2.0, so you can self-host with Docker Compose at no license cost. A fully managed Powabase Cloud handles updates, backups, and scaling, and an Enterprise edition adds a supported Kubernetes deployment with SLAs and private hosting. Public fixed price points are not listed on the homepage; contact the team for cloud and enterprise quotes.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [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) |
| 2 | [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) |
| 3 | [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) |
| 4 | [Mastra](https://openaitools.app/tool/mastra) | 318,954 | -5% | Freemium, Contact for Pricing | The TypeScript framework for building, deploying, and observing AI agents | [.md](https://openaitools.app/tool/mastra.md) |
| 5 | [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) |
| 6 | [Browserbase](https://openaitools.app/tool/browserbase) | 283,597 | -8% | Freemium | Cloud browsers and web APIs for AI agents | [.md](https://openaitools.app/tool/browserbase.md) |
| 7 | [Agent 37](https://openaitools.app/tool/agent-37) | 180,030 | +24.2% | Free Trial, Contact for Pricing | The low-cost cloud sandbox where AI agents actually live | [.md](https://openaitools.app/tool/agent-37.md) |
| 8 | [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) |
| 9 | [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) |
| 10 | [Coder](https://openaitools.app/tool/coder) | 149,417 | -12.8% | Free Trial, Contact for Pricing, Free | Self-hosted cloud development environments and AI coding agents for enterprise teams | [.md](https://openaitools.app/tool/coder.md) |

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

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