# Dagster vs Weave (WorkWeave)

Dagster records 105,563 monthly visits with -18.5% month-over-month growth and Free Trial, Paid, Contact for Pricing pricing. Weave (WorkWeave) records 13,482 monthly visits with -36.8% growth and Flexible pricing.

| Metric | [Dagster](https://openaitools.app/tool/dagster) | [Weave (WorkWeave)](https://openaitools.app/tool/workweave) |
| :--- | :--- | :--- |
| Website URL | https://www.dagster.io | https://weaveos.com |
| Categories | AI Developer Tools, AI Workflow, AI For Data Analytics, AI Productivity Tools | AI Developer Tools, AI For Data Analytics, AI Productivity Tools |
| Pricing Model | Free Trial, Paid, Contact for Pricing | Flexible |
| Monthly Visits | 105,563 | 13,482 |
| MoM Growth Rate | -18.5% | -36.8% |
| Primary Market | China | United States |
| Direct Visits | 25,739 | 11,248 |
| Review Score | 4.4 | 4.3 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Dagster

Dagster approaches orchestration from the output side. Instead of defining a pipeline as a sequence of tasks that either finish or fail, you declare the data assets you want to produce and their dependencies. Dagster then handles scheduling, backfills, partitions and retries, and — because it knows which asset each run touched — it can tell you automatically what downstream data is affected when something breaks. That asset graph is also what generates lineage and data health views without bolting on a separate catalog.

The platform covers the full DataOps loop. Orchestration runs asset-based pipelines across dbt, Snowflake, Fivetran, Spark, Python and other tools; observability surfaces lineage, freshness, dependencies and failures across the whole stack; and Dagster AI turns that accumulated context into diagnoses and actions. For organizations running data agents, a Compass layer lets teams build governed agents on top of trusted workflows. Deployment is flexible: Dagster+ managed cloud, hybrid where compute stays in your own infrastructure while the control plane is hosted, or fully self-hosted open source.

Dagster's positioning against Apache Airflow rests on that asset-centric philosophy — Airflow tells you a job failed, Dagster aims to tell you which asset broke, why, and what depends on it. The project was developed by Dagster Labs and is now part of Prefect, which has committed to continuing the platform; the open-source core remains available on GitHub.

**Pricing & Plans:** Freemium and open source. The core orchestration framework is free and self-hostable under an open-source licence, and there is a free entry tier for Dagster+. Paid team and business plans scale with usage, while enterprise deployments — branch deployments, hybrid compute, governance and SSO — are quoted through sales.

[Profile (Markdown)](https://openaitools.app/tool/dagster.md)

## Weave (WorkWeave)

Weave — known in earlier listings as WorkWeave — is an engineering intelligence platform built around a specific thesis: that AI has changed how software gets written, and that traditional delivery metrics no longer capture what is happening. Weave combines large language models with domain-specific machine learning to analyse code artifacts and infer how much work was done, how good it is, and how much of it AI contributed. It reports this alongside familiar frameworks such as DORA and SPACE.

The platform gathers signals from commits, pull requests, reviews, deployments and AI tool telemetry. That mix powers a set of dashboards covering AI-assisted merge rates, quality scores, per-engineer AI usage and overall team output, plus token and prompt-spend intelligence that connects AI cost to engineering results and benchmarks you against other organisations. An agent named Wooly answers natural-language questions about your teams and delivery cycles, citing the underlying records rather than producing generic advice.

A distinguishing capability is the Weave Router (also marketed under the name Astra), which sits between your coding clients and model providers. It classifies each prompt and routes it to the model offering the best quality-per-token, learning from feedback across the team. Installation is a single command that detects your clients and points them at the router proxy. The company reports 500+ engineering organisations, 2M+ pull requests analysed and 25k+ engineers measured, and states SOC 2 Type II certification, GDPR and HIPAA compliance, SSO and SCIM support.

**Pricing & Plans:** Freemium with enterprise tiers. Weave offers a free starting path and paid business plans, with enterprise options adding SSO, SCIM provisioning and expanded compliance. Exact figures are published on the Weave pricing page; teams at scale typically book a demo for a tailored quote.

- **Engineering intelligence dashboards:** Brings AI metrics, DORA and SPACE-based benchmarks and developer feedback into one view so you can see where work stalls from prompt to production.
- **AI adoption and ROI analytics:** Relates AI-assisted usage to merges, quality and cost, with per-engineer AI usage and AI score reporting plus benchmarks against 1,000+ organisations.
- **Token and cost intelligence:** Connects token and prompt spend to engineering output so you can see what you are getting for every AI dollar spent.
- **Coding agent model router:** Weave Router classifies each prompt and routes it to the model with the best quality-per-token, learning from team feedback over time.
- **Wooly AI agent and MCP access:** An AI engineering agent that answers questions about your teams and delivery, with every answer grounded in and citing your own records.

**Strengths:** Measures AI's contribution to engineering output rather than just counting activity; Combines AI telemetry, DORA/SPACE metrics and cost data in one platform; The router can cut model spend by directing prompts to cheaper models that still meet quality bar; Wooly answers cite your own records, which suits executive reporting

**Limitations:** Set up as an enterprise-grade platform, so pricing conversations and rollout suit larger engineering organisations; Meaningful insight depends on connecting your repositories, CI/CD and AI tooling — the value grows with how much data you feed it; Some features sit in the emerging 'AI code attribution' space where measurement methodology is still contentious; Requires organisational buy-in, since it is explicitly a tool for measuring developer work

[Profile (Markdown)](https://openaitools.app/tool/workweave.md)

## Frequently Asked Questions

### How do Dagster and Weave (WorkWeave) compare in monthly traffic?

Dagster has 105,563 monthly visits, while Weave (WorkWeave) has 13,482. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Dagster has a month-over-month growth rate of -18.5%; Weave (WorkWeave) has -36.8%.

### How does pricing compare?

Dagster: Free Trial, Paid, Contact for Pricing. Freemium and open source. The core orchestration framework is free and self-hostable under an open-source licence, and there is a free entry tier for Dagster+. Paid team and business plans scale with usage, while enterprise deployments — branch deployments, hybrid compute, governance and SSO — are quoted through sales. Weave (WorkWeave): Flexible. Freemium with enterprise tiers. Weave offers a free starting path and paid business plans, with enterprise options adding SSO, SCIM provisioning and expanded compliance. Exact figures are published on the Weave pricing page; teams at scale typically book a demo for a tailored quote.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Zapier](https://openaitools.app/tool/zapier-com) | 5,065,248 | +0.4% | Freemium, Free Trial, Paid | Automate work across thousands of apps — no code required | [.md](https://openaitools.app/tool/zapier-com.md) |
| 2 | [n8n](https://openaitools.app/tool/n8n) | 4,522,449 | -7.4% | Freemium | Open-source workflow automation built for AI agents and technical teams | [.md](https://openaitools.app/tool/n8n.md) |
| 3 | [Dify](https://openaitools.app/tool/dify-ai) | 819,691 | -15% | Freemium | Build, deploy, and govern production-ready agentic AI workflows | [.md](https://openaitools.app/tool/dify-ai.md) |
| 4 | [Labelbox](https://openaitools.app/tool/labelbox) | 762,803 | -22.8% | Contact for Pricing | The environments frontier AI trains on, and the agents that do the recurring work | [.md](https://openaitools.app/tool/labelbox.md) |
| 5 | [Warp](https://openaitools.app/tool/warp-ai) | 657,372 | -9.3% | Freemium, Contact for Pricing | AI-powered terminal and agentic software factory for development teams | [.md](https://openaitools.app/tool/warp-ai.md) |
| 6 | [Convex](https://openaitools.app/tool/convex) | 390,417 | -18.7% | Freemium, Paid | Reactive TypeScript backend with database, functions and AI gateway | [.md](https://openaitools.app/tool/convex.md) |
| 7 | [Weights & Biases (CoreWeave Forge)](https://openaitools.app/tool/prompts) | 315,624 | -80.2% | Freemium, Contact for Pricing, Free | Track, evaluate, and ship AI models and agents in one connected environment. | [.md](https://openaitools.app/tool/prompts.md) |
| 8 | [Tines](https://openaitools.app/tool/tines) | 273,260 | +24.4% | Freemium, Contact for Pricing | A secure environment where teams build, deploy and govern AI agents, apps and automations | [.md](https://openaitools.app/tool/tines.md) |
| 9 | [Activepieces](https://openaitools.app/tool/activepieces) | 258,553 | +1.5% | Freemium | Open-source AI automation that unifies agents, flows and 770+ app integrations | [.md](https://openaitools.app/tool/activepieces.md) |
| 10 | [Airbyte](https://openaitools.app/tool/airbyte) | 151,332 | -18.6% | Freemium, Free Trial, Paid | Open-source data integration engineered for AI agents and analytics | [.md](https://openaitools.app/tool/airbyte.md) |

---
Source: https://openaitools.app/compare/dagster-vs-workweave

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)