Polygres VS Panofy
Polygres VS Panofy 对比，Polygres 和 Panofy 有什麼區別？
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總結
Polygres 總結
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 著陸頁
Panofy 總結
Panofy 著陸頁
比較詳情
Polygres 詳細信息
| 類別 | AI 開發者工具, AI 代理, AI 知識圖譜, AI API, AI搜尋引擎 |
| Polygres 網站 | https://polygres.com?utm_source=toolify |
| 添加時間 | 2026年8月26日 |
| Polygres 定價 | -- |
Panofy 詳細信息
| 類別 | AI 開發者工具, AI 代理 |
| Panofy 網站 | https://panofy.ai?utm_source=Toolify&utm_medium=referral&utm_campaign=product_launch |
| 添加時間 | 2026年4月14日 |
| Panofy 定價 | -- |
使用對比
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.
如何使用Panofy？
Activating an Invite Code After registering on the homepage, you will automatically be added to the invite code waitlist. Check your email for your invite code. Training Your Agent Training is the core step in Panofy. Once training is complete, your agent retains the role definition, task scope, and output requirements you have set, and applies them consistently in every subsequent conversation — no need to re-explain the background each time. 1. In the Agent Workspace, click "+ New Agent" in the top-right corner to begin the creation process. 2. Name your agent based on its intended function — for example, "TweetForge". 3. In the training input field, provide instructions or knowledge content for your agent. Define its role, task scope, output format requirements, and tone preferences. 4. Upload files to accelerate knowledge building. Suitable materials include SOPs, business guidelines, evaluation frameworks, and reference examples. 5. Click "Submit" to begin training. You will be automatically redirected to the Agent Workspace, where training progress updates in real time. 6. Once training is complete, the agent's status changes from "Training" to "Ready". You can then proceed to the next step. Assigning Tasks to Your Agent Once training is complete, your agent has internalized its setup and is ready to receive and execute task instructions. Executing a Task 1. In the Agent Workspace, click on the relevant agent to open the conversation interface. 2. Enter your task instructions in the input box and send. The agent will begin executing the task automatically. 3. Results are displayed in real time in the conversation window and simultaneously saved to the "Output" panel on the left. Creating a New Task 1. Click "New Task" in the right-hand navigation bar to create an additional task for the same agent. 2. For complex tasks, the agent will automatically generate a task plan listing each step. You can then choose to execute immediately, schedule execution, or revise the plan. 3. Once execution is confirmed, you can monitor the progress of each sub-task in real time. 4. Click "Import" in the right-hand navigation bar to bring in an existing task plan from another complex task. This allows established workflows to be saved and reused directly. Inviting Collaborators and Sharing 1. Click "Invite" in the right-hand navigation bar to generate an invite link. Anyone with the link can use your trained agent directly, with any credits consumed charged to their own account. You can configure whether to include access to external tools and whether to require a passcode. 2. Click the share icon above the conversation to generate a shareable link for the task record. You can set visibility to "Anyone with the link" or "Only me", and optionally enable playback mode so external viewers can replay the task without needing to register. You're ready to start. Create your first agent, train it, and let it become a genuine part of how you work. The more you put in, the better it gets.
比較 Polygres 和 Panofy 的優點
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
Panofy 的核心功能
- - Agent Training — Train a reusable AI agent with a single sentence. No more rewriting context every session. Your agent carries your instructions forward, reducing communication overhead and token consumption.
- - Long-Term Memory — As your agent works, it automatically learns experience and reflects on mistakes. The more you use it, the better it understands you.
- - Agent Swarm — Manage an entire team of AI agents from one platform. Each agent maintains its own dedicated knowledge base and memory, ready to handle its specialized role.
比較用例
Polygres 的用例
- 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
Panofy 的用例
- You can train a content assistant that understands your brand voice and continuously generates on-tone copy and content ideas.
- You can upload your company's SOPs and product documentation to turn an agent into an onboarding guide for new hires or a customer-facing support bot.
- You can define a competitive analysis framework and have an agent produce structured reports to that same standard, every time.
- What these scenarios share is that the agent doesn't just answer once — it becomes a stable, long-term part of how you work.
Polygres 和 Panofy 之間的計劃不同
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.
Panofy
$20 / PLUS
$200 / PRO
Polygres 的流量
Polygres 是月访问量為 29.2K 且平均訪問時長為 00:00:44 的工具。 Polygres 的每次訪問頁數為 1.61，跳出率為 68.04%。
最新網站流量
| 月訪問量 | 29.2K |
| 平均訪問時長 | 00:00:44 |
| 每次訪問頁數 | 1.61 |
| 跳出率 | 68.04% |
Panofy 的流量
Panofy 是月访问量為 0 且平均訪問時長為 00:00:00 的工具。 Panofy 的每次訪問頁數為 0.00，跳出率為 0.00%。
最新網站流量
| 月訪問量 | 0 |
| 平均訪問時長 | 00:00:00 |
| 每次訪問頁數 | 0.00 |
| 跳出率 | 0.00% |
地理流量
The top 3 countries/regions for Polygres are:United States 84.49%, India 15.16%, Mexico 0.34%
Top 3 Countries/regions
 | 84.49% |
 | 15.16% |
 | 0.34% |
地理流量
對不起，沒有數據
網站流量來源
Polygres 的 6 個主要流量來源是：直接 43.28%, vs_sourcesSocialOrganic 34.37%, vs_sourcesSearchOrganic 14.81%, 引薦 4.00%, 郵件 1.48%, vs_sourcesGenAi 0.93%, vs_sourcesDisplayAds 0.49%, vs_sourcesAffiliate 0.25%, vs_sourcesSearchPaid 0.25%, vs_sourcesSocialPaid 0.12%
直接 | 43.28% |
vs_sourcesSocialOrganic | 34.37% |
vs_sourcesSearchOrganic | 14.81% |
引薦 | 4.00% |
郵件 | 1.48% |
vs_sourcesGenAi | 0.93% |
vs_sourcesDisplayAds | 0.49% |
vs_sourcesAffiliate | 0.25% |
vs_sourcesSearchPaid | 0.25% |
vs_sourcesSocialPaid | 0.12% |
網站流量來源
Panofy 的 6 個主要流量來源是：郵件 0, vs_sourcesGenAi 0, 直接 0, vs_sourcesAffiliate 0, 引薦 0, vs_sourcesDisplayAds 0, vs_sourcesSearchPaid 0, vs_sourcesSocialPaid 0, vs_sourcesSearchOrganic 0, vs_sourcesSocialOrganic 0
郵件 | 0 |
vs_sourcesGenAi | 0 |
直接 | 0 |
vs_sourcesAffiliate | 0 |
引薦 | 0 |
vs_sourcesDisplayAds | 0 |
vs_sourcesSearchPaid | 0 |
vs_sourcesSocialPaid | 0 |
vs_sourcesSearchOrganic | 0 |
vs_sourcesSocialOrganic | 0 |
Polygres 或 Panofy哪個更好？
Polygres 可能比 Panofy 更受歡迎。如您所見，Polygres 每月有 29.2K 次訪問，而 Panofy 每月有 0 次訪問。 所以更多的人選擇Polygres。 因此，人們很可能會在社交平台上更多地推薦 Polygres。
Polygres 的平均訪問持續時間為 00:00:44，而 Panofy 的平均訪問持續時間為 00:00:00。 此外，Polygres 的每次訪問頁面為 1.61，跳出率為 68.04%。 Panofy 的每次訪問頁面為 0.00，跳出率為 0.00%。
Polygres 的主要用戶是United States, India, Mexico，分佈如下：84.49%, 15.16%, 0.34%。
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