Dagster VS exe.dev
Dagster VS exe.dev对比，Dagster 和 exe.dev 有什么区别？
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总结
Dagster 总结
The cloud-native orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability.
Dagster 着陆页
exe.dev 总结
exe.dev 着陆页
比较详细信息
Dagster 详细信息
| 类别 | AI开发者工具, AI工作流, AI数据分析, AI生产力工具 |
| Dagster 网站 | https://www.dagster.io?utm_source=toolify |
| 添加时间 | 2025年12月12日 |
| Dagster 定价 | -- |
exe.dev 详细信息
| 类别 | AI开发者工具, AI智能体, AI应用构建器 |
| exe.dev 网站 | https://exe.dev?utm_source=toolify |
| 添加时间 | 2026年8月21日 |
| exe.dev 定价 | -- |
使用情况比较
如何使用 Dagster？
To use Dagster, you can get started with a free 30-day trial or book a demo. The platform allows you to develop and test pipelines, monitor data quality, track complete data lineage, and leverage metadata and source observability. It supports testing code in any development stage locally, enabling automatic deployment to staging environments and confident shipping of data and AI products faster.
如何使用 exe.dev？
Create an exe.dev account and choose a plan, then launch a VM using the exe.dev command-line interface or web interface. Use commands such as "ssh exe.dev new" to create a machine, optionally specifying its name, image, prompt, or disk size. Once ready, connect through SSH, access applications through HTTPS proxy URLs, or use Shelley as a built-in web coding agent. Teams can manage users and permissions through administrative controls and SSO.
比较 Dagster 和 exe.dev 的优势
Dagster的核心功能
- Data Orchestration
- Integrated Lineage and Observability
- Asset-based Orchestration
- Best-in-class Testability (local testing, branch deployments)
- Data Catalog & Quality
- Cost Tracking and Insights
exe.dev的核心功能
- Instant disposable and persistent Linux VMs
- SSH access, HTTPS application proxying, root privileges, apt, and systemd
- Built-in Shelley web coding agent for developers and AI agents
- API-first VM creation and management
- Private-by-default infrastructure with IAM-based sharing
- Configurable CPU, memory, and disk resources
- Pooled resources that support multiple VMs and burstable team capacity
- Support for development, sandbox, VPS, data analysis, and production workloads
比较使用案例
Dagster的使用案例
- ETL/ELT Pipelines
- AI & Machine Learning Workflows
- Data Modernization
- Building Data Products
- Building Trustworthy AI Analytics
exe.dev的使用案例
- Create disposable Linux sandboxes for AI coding agents
- Build and host web applications on persistent cloud VMs
- Develop remotely over SSH from a laptop, tablet, or phone
- Give an AI agent a fresh machine and a natural-language coding task
- Run data analysis workflows using SQL and visualization tools
- Create shared team development environments with IAM and SSO
- Prototype applications before deploying them to production
- Host lightweight services with HTTPS access and persistent storage
Dagster和exe.dev的不同计划
Dagster
$10 per month
Perfect for personal projects and building simple pipelines. Includes 7.5k credits/month, 1 User, 1 Code location, 1 Deployment, 30-day free trial.
$100 per month
For production pipelines that scale, with role-based access control and catalog search. Includes 30k credits/month, Up to 3 Users, 5 Code locations, 1 Deployment, Catalog Search, 30-day free trial.
Contact Sales
For building and scaling large-scale data platforms. Includes Unlimited code locations, Unlimited deployments, Cost Tracking and Insights, Personalized Onboarding Support, Private Slack channel, Uptime SLAs, Custom Security Questionnaires.
exe.dev
$20/month
50 VMs, 100 GB pooled disk, and 200 GB data transfer
$25/user/month
50 VMs per user, 100 GB pooled disk, 250 GB data transfer, admin and user management, and SSO
$35.84/hour
512 vCPU, 2,048 GB RAM, thousands of VMs with pooled disks, admin and user management, SSO, and AWS VPC integration
$0.08/GB/month
Charged for disk usage beyond the included allocation
$0.05/GB/month
Charged for data transfer beyond the included allocation
Dagster的流量
Dagster 是月访问量为 146.1K 且平均访问时长为 00:00:54 的工具。 Dagster 的每次访问页数为 1.88，跳出率为 47.02%。
最新流量情况
| 月访问量 | 146.1K |
| 平均·访问时长 | 00:00:54 |
| 每次访问页数 | 1.88 |
| 跳出率 | 47.02% |
exe.dev的流量
exe.dev 是月访问量为 179.0K 且平均访问时长为 00:01:42 的工具。 exe.dev 的每次访问页数为 1.89，跳出率为 51.21%。
最新流量情况
| 月访问量 | 179.0K |
| 平均·访问时长 | 00:01:42 |
| 每次访问页数 | 1.89 |
| 跳出率 | 51.21% |
地理位置
Dagster 的前 5 个国家/地区是：United States 16.85%, China 13.31%, Vietnam 8.01%, Austria 6.04%, Pakistan 4.35%
Top 5 国家/地区
 | 16.85% |
 | 13.31% |
 | 8.01% |
 | 6.04% |
 | 4.35% |
地理位置
exe.dev 的前 5 个国家/地区是：United States 36.06%, China 9.83%, Germany 9.21%, Thailand 7.32%, India 7.02%
Top 5 国家/地区
| 36.06% |
| 9.83% |
 | 9.21% |
 | 7.32% |
 | 7.02% |
流量来源
Dagster 的 6 个主要流量来源是：vs_sourcesSearchOrganic 41.52%, 直接访问 19.68%, 外链引荐 18.52%, vs_sourcesSocialOrganic 10.39%, vs_sourcesSearchPaid 5.75%, vs_sourcesGenAi 1.61%, 邮件 1.07%, vs_sourcesDisplayAds 0.80%, vs_sourcesSocialPaid 0.66%, vs_sourcesAffiliate 0.00%
vs_sourcesSearchOrganic | 41.52% |
直接访问 | 19.68% |
外链引荐 | 18.52% |
vs_sourcesSocialOrganic | 10.39% |
vs_sourcesSearchPaid | 5.75% |
vs_sourcesGenAi | 1.61% |
邮件 | 1.07% |
vs_sourcesDisplayAds | 0.80% |
vs_sourcesSocialPaid | 0.66% |
vs_sourcesAffiliate | 0.00% |
流量来源
exe.dev 的 6 个主要流量来源是：直接访问 44.34%, vs_sourcesSocialOrganic 38.73%, 外链引荐 7.73%, vs_sourcesSearchOrganic 4.58%, 邮件 2.97%, vs_sourcesGenAi 0.88%, vs_sourcesSocialPaid 0.77%, vs_sourcesAffiliate 0.00%, vs_sourcesDisplayAds 0.00%, vs_sourcesSearchPaid 0.00%
直接访问 | 44.34% |
vs_sourcesSocialOrganic | 38.73% |
外链引荐 | 7.73% |
vs_sourcesSearchOrganic | 4.58% |
邮件 | 2.97% |
vs_sourcesGenAi | 0.88% |
vs_sourcesSocialPaid | 0.77% |
vs_sourcesAffiliate | 0.00% |
vs_sourcesDisplayAds | 0.00% |
vs_sourcesSearchPaid | 0.00% |
Dagster 或 exe.dev哪个更好？
exe.dev 可能比 Dagster 更受欢迎。如您所见，Dagster 每月有 146.1K 次访问，而 exe.dev 每月有 179.0K 次访问。 所以更多的人选择了exe.dev。 因此，人们很可能会在社交平台上更多地推荐 exe.dev。
Dagster 的平均访问持续时间为 00:00:54，而 exe.dev 的平均访问持续时间为 00:01:42。 此外，Dagster 的每次访问页面为 1.88，跳出率为 47.02%。 exe.dev 的每次访问页面为 1.89，跳出率为 51.21%。
Dagster 的主要用户是United States, China, Vietnam, Austria, Pakistan，分布如下：16.85%, 13.31%, 8.01%, 6.04%, 4.35%。
exe.dev 的主要用户是 United States, China, Germany, Thailand, India，分布如下：36.06%, 9.83%, 9.21%, 7.32%, 7.02%。
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