Vellum AI VS Polygres
Vellum AI VS Polygres对比，Vellum AI 和 Polygres 有什么区别？
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总结
Vellum AI 总结
Vellum AI 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
Vellum AI 详细信息
| 类别 | AI开发者工具, AI工作流, 提示词工程 |
| Vellum AI 网站 | https://www.vellum.ai/sp/showcase?utm_source=toolify |
| 添加时间 | 2023年11月28日 |
| Vellum AI 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 Vellum AI？
Vellum AI can be used to build AI systems, from basic prompts to agentic workflows, using its Workflows IDE. Users can define, edit, and run code or UI, and push/pull changes between the two. The platform also allows for evaluating AI system quality with pre-made or custom-built metrics and deploying AI updates with easy integration and one-click deploy.
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 Vellum AI 和 Polygres 的优势
Vellum AI的核心功能
- Orchestration
- SDK
- Prompting
- Evaluations
- Retrieval
- Deployment
- Observability
- Visual Workflow Builder
- LLM Playground
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
Vellum AI的使用案例
- Building agentic AI workflows
- Generating a LinkedIn post from a URL
- Testing prompt designs and model configurations
- Evaluating AI system quality
- Deploying AI updates
- Monitoring AI decisions
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
Vellum AI和Polygres的不同计划
Vellum AI
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.
Vellum AI的流量
Vellum AI 是月访问量为 416.0K 且平均访问时长为 00:01:07 的工具。 Vellum AI 的每次访问页数为 2.13，跳出率为 49.73%。
最新流量情况
| 月访问量 | 416.0K |
| 平均·访问时长 | 00:01:07 |
| 每次访问页数 | 2.13 |
| 跳出率 | 49.73% |
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
Vellum AI 的前 5 个国家/地区是：United States 23.43%, India 7.91%, Germany 3.33%, Brazil 3.19%, China 3.11%
Top 5 国家/地区
 | 23.43% |
 | 7.91% |
 | 3.33% |
 | 3.19% |
 | 3.11% |
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
Vellum AI 的 6 个主要流量来源是：vs_sourcesSearchOrganic 65.68%, 直接访问 21.48%, 外链引荐 7.57%, vs_sourcesGenAi 2.48%, vs_sourcesSocialOrganic 1.95%, vs_sourcesDisplayAds 0.50%, 邮件 0.24%, vs_sourcesSearchPaid 0.10%, vs_sourcesAffiliate 0.00%, vs_sourcesSocialPaid 0.00%
vs_sourcesSearchOrganic | 65.68% |
直接访问 | 21.48% |
外链引荐 | 7.57% |
vs_sourcesGenAi | 2.48% |
vs_sourcesSocialOrganic | 1.95% |
vs_sourcesDisplayAds | 0.50% |
邮件 | 0.24% |
vs_sourcesSearchPaid | 0.10% |
vs_sourcesAffiliate | 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% |
Vellum AI 或 Polygres哪个更好？
Vellum AI 可能比 Polygres 更受欢迎。如您所见，Vellum AI 每月有 416.0K 次访问，而 Polygres 每月有 11.6K 次访问。 所以更多的人选择了Vellum AI。 因此，人们很可能会在社交平台上更多地推荐 Vellum AI。
Vellum AI 的平均访问持续时间为 00:01:07，而 Polygres 的平均访问持续时间为 00:00:12。 此外，Vellum AI 的每次访问页面为 2.13，跳出率为 49.73%。 Polygres 的每次访问页面为 1.40，跳出率为 92.09%。
Vellum AI 的主要用户是United States, India, Germany, Brazil, China，分布如下：23.43%, 7.91%, 3.33%, 3.19%, 3.11%。
Polygres 的主要用户是 United States，分布如下：100.00%。
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