Schematic VS Polygres
Schematic VS Polygres对比，Schematic 和 Polygres 有什么区别？
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总结
Schematic 总结
Schematic 着陆页
Polygres 总结
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 着陆页
比较详细信息
Schematic 详细信息
| 类别 | AI开发者工具, AI销售, AI生产力工具, 无代码与低代码开发 |
| Schematic 网站 | https://www.schematichq.com?utm_source=toolify |
| 添加时间 | 2025年7月25日 |
| Schematic 定价 | -- |
Polygres 详细信息
| 类别 | AI开发者工具, AI智能体, AI知识图谱, 人工智能接口, AI搜索引擎 |
| Polygres 网站 | https://polygres.com?utm_source=toolify |
| 添加时间 | 2026年8月26日 |
| Polygres 定价 | -- |
使用情况比较
如何使用 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.
如何使用 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.
比较 Schematic 和 Polygres 的优势
Schematic的核心功能
- 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#)
Polygres的核心功能
- 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
比较使用案例
Schematic的使用案例
- 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
Polygres的使用案例
- 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
Schematic和Polygres的不同计划
Schematic
对不起，没有数据
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的流量
Schematic 是月访问量为 29.5K 且平均访问时长为 00:01:08 的工具。 Schematic 的每次访问页数为 2.45，跳出率为 37.37%。
最新流量情况
| 月访问量 | 29.5K |
| 平均·访问时长 | 00:01:08 |
| 每次访问页数 | 2.45 |
| 跳出率 | 37.37% |
Polygres的流量
Polygres 是月访问量为 11.6K 且平均访问时长为 00:00:12 的工具。 Polygres 的每次访问页数为 1.40，跳出率为 92.09%。
最新流量情况
| 月访问量 | 11.6K |
| 平均·访问时长 | 00:00:12 |
| 每次访问页数 | 1.40 |
| 跳出率 | 92.09% |
地理位置
Schematic 的前 5 个国家/地区是：United States 20.34%, Egypt 14.20%, India 8.38%, Vietnam 7.53%, Brazil 5.31%
Top 5 国家/地区
 | 20.34% |
 | 14.20% |
 | 8.38% |
 | 7.53% |
 | 5.31% |
地理位置
Polygres 的前 1 个国家/地区是：United States 100.00%
Top 1 国家/地区
| 100.00% |
流量来源
Schematic 的 6 个主要流量来源是：直接访问 69.47%, vs_sourcesSearchOrganic 16.29%, 外链引荐 11.05%, vs_sourcesDisplayAds 1.30%, vs_sourcesSocialOrganic 1.17%, vs_sourcesGenAi 0.74%, 邮件 0.00%, vs_sourcesAffiliate 0.00%, vs_sourcesSearchPaid 0.00%, vs_sourcesSocialPaid 0.00%
直接访问 | 69.47% |
vs_sourcesSearchOrganic | 16.29% |
外链引荐 | 11.05% |
vs_sourcesDisplayAds | 1.30% |
vs_sourcesSocialOrganic | 1.17% |
vs_sourcesGenAi | 0.74% |
邮件 | 0.00% |
vs_sourcesAffiliate | 0.00% |
vs_sourcesSearchPaid | 0.00% |
vs_sourcesSocialPaid | 0.00% |
流量来源
Polygres 的 6 个主要流量来源是：直接访问 57.14%, vs_sourcesSocialOrganic 21.37%, vs_sourcesSearchOrganic 13.47%, 外链引荐 5.27%, 邮件 2.75%, vs_sourcesGenAi 0.00%, vs_sourcesAffiliate 0.00%, vs_sourcesDisplayAds 0.00%, vs_sourcesSearchPaid 0.00%, vs_sourcesSocialPaid 0.00%
直接访问 | 57.14% |
vs_sourcesSocialOrganic | 21.37% |
vs_sourcesSearchOrganic | 13.47% |
外链引荐 | 5.27% |
邮件 | 2.75% |
vs_sourcesGenAi | 0.00% |
vs_sourcesAffiliate | 0.00% |
vs_sourcesDisplayAds | 0.00% |
vs_sourcesSearchPaid | 0.00% |
vs_sourcesSocialPaid | 0.00% |
Schematic 或 Polygres哪个更好？
Schematic 可能比 Polygres 更受欢迎。如您所见，Schematic 每月有 29.5K 次访问，而 Polygres 每月有 11.6K 次访问。 所以更多的人选择了Schematic。 因此，人们很可能会在社交平台上更多地推荐 Schematic。
Schematic 的平均访问持续时间为 00:01:08，而 Polygres 的平均访问持续时间为 00:00:12。 此外，Schematic 的每次访问页面为 2.45，跳出率为 37.37%。 Polygres 的每次访问页面为 1.40，跳出率为 92.09%。
Schematic 的主要用户是United States, Egypt, India, Vietnam, Brazil，分布如下：20.34%, 14.20%, 8.38%, 7.53%, 5.31%。
Polygres 的主要用户是 United States，分布如下：100.00%。
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