# Airbyte vs Dagster Airbyte records 151,332 monthly visits with -18.6% month-over-month growth and Freemium, Free Trial, Paid pricing. Dagster records 105,563 monthly visits with -18.5% growth and Free Trial, Paid, Contact for Pricing pricing. | Metric | [Airbyte](https://openaitools.app/tool/airbyte) | [Dagster](https://openaitools.app/tool/dagster) | | :--- | :--- | :--- | | Website URL | https://airbyte.com | https://www.dagster.io | | Categories | Large Language Models (LLMs), AI Developer Tools, AI Workflow, No-Code&Low-Code | AI Developer Tools, AI Workflow, AI For Data Analytics, AI Productivity Tools | | Pricing Model | Freemium, Free Trial, Paid | Free Trial, Paid, Contact for Pricing | | Monthly Visits | 151,332 | 105,563 | | MoM Growth Rate | -18.6% | -18.5% | | Primary Market | United States | China | | Direct Visits | 64,168 | 25,739 | | Review Score | 4.6 | 4.4 | | Saved Count | 0 | 0 | | Supported Platforms | Website | Website | ## Airbyte Airbyte began as an open-source alternative to proprietary ELT pipelines and has grown into a full data movement platform. Teams use it to extract data from SaaS apps, databases, and APIs, load it into warehouses or lakes, and keep it synchronized on a schedule. With more than 700 prebuilt connectors and a connector builder for custom sources, it covers the long tail of data sources that commercial platforms often ignore, and it can run entirely inside your own VPC if data residency matters. More recently Airbyte has leaned into the AI era by promoting an MCP server and a context layer concept: rather than letting agents reach into production systems directly, you land data in your warehouse first and then let agents query it with inherited access controls. This keeps governance, permissions, and lineage intact while still giving agents the fresh context they need. The platform is available in three deployment flavors. Airbyte Cloud is fully managed and starts free, Airbyte Hybrid lets Airbyte run the orchestration control plane while your pipelines execute in your own cloud or data center, and Airbyte Core is the open-source engine you can host yourself. Pricing for the commercial tiers is usage-based against rows or credits and scales with your sync volume, with enterprise contracts available for regulated organizations. **Pricing & Plans:** Free tier plus usage-based paid plans; Airbyte Cloud starts free, Hybrid and Enterprise are quoted per volume or contract. Exact rates change, so check the official pricing page. - **700+ prebuilt connectors:** Connect databases, SaaS tools, files, and APIs to warehouses, lakes, and other destinations without writing ingestion code for each source. - **Connector Builder:** Define a custom connector declaratively in minutes when no prebuilt one exists, then use it like any other connector in your pipelines. - **MCP and context layer:** Serve warehouse data to AI agents through an MCP server with inherited access controls, so agents get context without bypassing governance. - **Flexible deployment:** Choose fully managed Cloud, a hybrid model where pipelines run in your own VPC, or the self-hosted open-source core. - **Open-source core:** The engine and connectors are open source, so you can self-host, extend, and audit the pipeline logic without vendor lock-in. **Strengths:** Very large connector library including niche and long-tail sources; Open-source core avoids total vendor lock-in and allows self-hosting; Strong deployment flexibility with cloud, hybrid, and self-managed options; Active MCP and context layer work makes it relevant for AI agent workflows **Limitations:** Usage-based pricing can grow quickly at high sync volumes; Self-hosting requires real operational effort to run and maintain at scale; Connector quality varies, so some sources need tuning or a custom build [Profile (Markdown)](https://openaitools.app/tool/airbyte.md) ## 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) ## Frequently Asked Questions ### How do Airbyte and Dagster compare in monthly traffic? Airbyte has 151,332 monthly visits, while Dagster has 105,563. Traffic estimates describe audience size, not product quality. ### How do their growth rates compare? Airbyte has a month-over-month growth rate of -18.6%; Dagster has -18.5%. ### How does pricing compare? Airbyte: Freemium, Free Trial, Paid. Free tier plus usage-based paid plans; Airbyte Cloud starts free, Hybrid and Enterprise are quoted per volume or contract. Exact rates change, so check the official pricing page. 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. ## 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 | [Dust](https://openaitools.app/tool/dust) | 547,217 | +1.8% | Contact for Pricing | Multiplayer AI where people and agents work side by side | [.md](https://openaitools.app/tool/dust.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 | [LlamaIndex](https://openaitools.app/tool/llamaindex) | 387,910 | +19.9% | Freemium, Contact for Pricing | Excels at parsing documents and preparing data for AI RAG, whereas Airbyte focuses on broad database syncing. | [.md](https://openaitools.app/tool/llamaindex.md) | | 8 | [Gumloop](https://openaitools.app/tool/gumloop) | 379,557 | -21.1% | Freemium, Paid, Contact for Pricing | Build, share, and control AI agents that actually do the work | [.md](https://openaitools.app/tool/gumloop.md) | | 9 | [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) | | 10 | [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) | --- Source: https://openaitools.app/compare/airbyte-vs-dagster More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)