How do their growth rates compare?

Polygres has a month-over-month growth rate of -52.3%; TinyFish has +199.7%.

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. TinyFish: Freemium, Contact for Pricing. Freemium and usage-based. Search and basic fetch are free with no search fee, while TinyAgent is billed per step, TinyBrowser per minute and TinyMonitor per check from a prepaid wallet; new users can claim a small free credit. Enterprise plans are custom — confirm current rates on the pricing page.

What are alternatives to Polygres and TinyFish?

Other tools in related categories include Claude, DeepSeek, OpenAI Platform, Google AI Studio, Salesforce Agentforce (formerly Einstein).

Polygres vs TinyFish — Traffic (4.02K vs 1.12M), Pricing & Verdict

Open AI Tools

Polygres vs TinyFish — Traffic (4.02K vs 1.12M), Pricing & Verdict | Open AI Tools

Side-by-Side Traffic & Specification Matrix

Dimension / Metric	Polygres	TinyFish
Official Domain	polygres.com	tinyfish.ai
Pricing Model	Freemium	Freemium, Contact for Pricing
Monthly Visits	4.02K (4,018)	1.12M (1,124,952)
MoM Traffic Delta	-4.41K (-52.3%)	+749.57K (+199.7%)
Primary Market & Share	🌐 Global (—)	🇺🇸 United States (27.4%)
Direct Visits / mo	1.61K	401.32K
User Rating	4.1	4.4
Supported Platforms	Website	Website

Polygres

Graph, vector and text retrieval for AI agents on your Postgres

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.

Strengths & Pros

+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