Schematic VS Polygres
Compare Schematic VS Polygres, what is the difference between Schematic and Polygres?
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Summarize
Schematic summarize
Schematic Landing Page
Polygres summarize
Polygres turns Postgres into working memory for AI agents. Retrieve structured rows, connected relationships, semantic matches, and full-text results through one hybrid API. All without a separate vector store, graph database, or sync pipeline. Build grounded agents over the data you already have, with relational, graph, and vector context joined at the source. Use the managed cloud or self-host with our open source components. Polygres is currently free to use, just sign up!
Polygres Landing Page
Compare Details
Schematic details
| Categories | AI Developer Tools, AI Sales, AI Productivity Tools, No-Code&Low-Code |
| Schematic Website | https://www.schematichq.com?utm_source=toolify |
| Added Time | July 25 2025 |
| Schematic Pricing | -- |
Polygres details
| Categories | AI Developer Tools, AI Agent, AI Knowledge Graph, AI API, AI Search Engine |
| Polygres Website | https://polygres.com?utm_source=toolify |
| Added Time | August 26 2026 |
| Polygres Pricing | -- |
Comparison of usage
How to use Schematic?
Developers integrate Schematic's SDKs and drop-in components (like customer portal, pricing table, checkout) into their product. Once integrated, GTM teams can use Schematic's platform to define, manage, and iterate on pricing models, plans, entitlements, feature access, and customer exceptions without needing engineering support or code deployments. Users can start by trying a demo or signing up for a free account.
How to use Polygres?
Create a Polygres managed instance or install the open-source components on an existing PostgreSQL database. Connect your schema and use the SDK or retrieval API to submit a natural-language query with options such as graph traversal depth, filters, and token limits. Polygres combines relational, graph, vector, and text results into one ranked, token-ready context block that can be passed directly to an AI agent.
Compare Pros between Schematic and Polygres
Core features of Schematic
- Metering & Pricing (Launch usage-based pricing, support any model)
- Plans & Entitlements (Manage plans, limits, trials, and customer journeys)
- Smart Flags (Roll out, entitle, gate, track usage, and monetize features)
- Billing Components (Drop-in customer portal, pricing table, checkout, element library)
- Insights (Identify upgrade opportunities and churn risks)
- Decoupling business logic from code
- Stripe integration
- SDKs for various languages (NextJs, NodeJs, Go, React, JS, Python, Java, C#)
Core features of Polygres
- Unified relational, graph, vector, and full-text retrieval
- Native graph traversal over existing PostgreSQL foreign keys
- Fused hybrid search with dense HNSW, sparse, filtered, and semantic retrieval
- Token-ready context assembly for grounded AI agents
- Shortest-path, neighborhood, relationship, and multi-hop graph queries
- Managed cloud hosting and open-source self-hosting
- PostgreSQL-native data retrieval without a separate vector store or sync pipeline
Compare Use Cases
Use cases for Schematic
- Launching a new product or add-on
- Layering self-serve onto sales-led models
- Adding sales-led on top of self-serve models
- Driving product-led expansion
- Testing a move upmarket
- Introducing usage-based or hybrid pricing
- Launching usage-based or credit-based pricing in days
- Implementing any pricing model without rebuilding billing stack
- Launching trials without engineering support
- Using paywalls to drive upgrades and expansions
- Issuing loyalty credits or entitlements to retain at-risk accounts
- Tracking usage and payments to act before churn hits
- Experimenting with pricing without waiting on developers
Use cases for Polygres
- Build grounded AI agents that retrieve customer records, orders, tickets, and related history
- Investigate failed transactions by combining semantic search with order, payment, and dispute relationships
- Create user-memory systems that retrieve relevant past interactions and connected data
- Query Wikipedia-scale datasets using hybrid indexes and graph relationships
- Provide support agents with ranked, database-backed context
- Develop recommendation and discovery systems using existing PostgreSQL data
Different Plan between Schematic and Polygres
Schematic
Sorry, there are no data
Polygres
$0 / forever
Open-source pgGraph and pgVector, runnable on any PostgreSQL instance, with community support.
$16 / month
Managed cloud database hosting with email and community Discord support. Currently free for now.
$256 / month minimum usage
Automated vertical and horizontal scaling, email and community Discord support, private Discord or Slack channel, and support hours from 8:00 AM to 5:00 PM.
$4,096 / month minimum usage
Coming soon. Includes dedicated database infrastructure, custom compliance, high availability, 24/7 support, and dedicated support and uptime SLAs.
Schematic's traffic
Schematic is the one with 29.5K monthly visits and 00:01:08 Avg.visit duration. Schematic has a Page per visit of 2.45 and a bounce rate of 37.37%.
Visit Over Time
| Monthly Visits | 29.5K |
| Avg·visit Duration | 00:01:08 |
| Page per Visit | 2.45 |
| Bounce Rate | 37.37% |
Polygres's traffic
Polygres is the one with 11.6K monthly visits and 00:00:12 Avg.visit duration. Polygres has a Page per visit of 1.40 and a bounce rate of 92.09%.
Visit Over Time
| Monthly Visits | 11.6K |
| Avg·visit Duration | 00:00:12 |
| Page per Visit | 1.40 |
| Bounce Rate | 92.09% |
Geography
The top 5 countries/regions for Schematic are:United States 20.34%, Egypt 14.20%, India 8.38%, Vietnam 7.53%, Brazil 5.31%
Top 5 Countries/regions
 | 20.34% |
 | 14.20% |
 | 8.38% |
 | 7.53% |
 | 5.31% |
Geography
The top 1 countries/regions for Polygres are:United States 100.00%
Top 1 Countries/regions
| 100.00% |
Traffic Sources
The 6 main sources of traffic to Schematic are:Direct 69.47%, vs_sourcesSearchOrganic 16.29%, Referrals 11.05%, vs_sourcesDisplayAds 1.30%, vs_sourcesSocialOrganic 1.17%, vs_sourcesGenAi 0.74%, Mail 0.00%, vs_sourcesAffiliate 0.00%, vs_sourcesSearchPaid 0.00%, vs_sourcesSocialPaid 0.00%
Direct | 69.47% |
vs_sourcesSearchOrganic | 16.29% |
Referrals | 11.05% |
vs_sourcesDisplayAds | 1.30% |
vs_sourcesSocialOrganic | 1.17% |
vs_sourcesGenAi | 0.74% |
Mail | 0.00% |
vs_sourcesAffiliate | 0.00% |
vs_sourcesSearchPaid | 0.00% |
vs_sourcesSocialPaid | 0.00% |
Traffic Sources
The 6 main sources of traffic to Polygres are:Direct 57.14%, vs_sourcesSocialOrganic 21.37%, vs_sourcesSearchOrganic 13.47%, Referrals 5.27%, Mail 2.75%, vs_sourcesGenAi 0.00%, vs_sourcesAffiliate 0.00%, vs_sourcesDisplayAds 0.00%, vs_sourcesSearchPaid 0.00%, vs_sourcesSocialPaid 0.00%
Direct | 57.14% |
vs_sourcesSocialOrganic | 21.37% |
vs_sourcesSearchOrganic | 13.47% |
Referrals | 5.27% |
Mail | 2.75% |
vs_sourcesGenAi | 0.00% |
vs_sourcesAffiliate | 0.00% |
vs_sourcesDisplayAds | 0.00% |
vs_sourcesSearchPaid | 0.00% |
vs_sourcesSocialPaid | 0.00% |
Which is better: Schematic or Polygres?
Schematic might be a bit more popular than Polygres.As you can see, Schematic has 29.5K monthly visits, while Polygres has 11.6K monthly visits. So more people choose Schematic. So the odds are that people will recommend Schematic more on social platforms.
Schematic has an Avg.visit duration of 00:01:08, while Polygres has an Avg.visit duration of 00:00:12. Also, Schematic has a page per visit of 2.45 and a Bounce Rate of 37.37%. Polygres has a page per visit of 1.40 and a Bounce Rate of 92.09%.
The main users of Schematic are United States, Egypt, India, Vietnam, Brazil, with the following distribution: 20.34%, 14.20%, 8.38%, 7.53%, 5.31%.
The main users of Polygres are United States, with the following distribution: 100.00%.
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