comparisons
CloudQuery vs Airbyte
Tim Armstrong •
CloudQuery vs Airbyte: A Comprehensive Comparison #
Data integration and movement is an ever-evolving landscape with many players and exciting developments in recent years. Choosing the right tool depends on the requirements, needs, and resources available. This blog will compare the pros and cons of CloudQuery vs Airbyte to help you make the best decision.
What is CloudQuery? #
CloudQuery is an open-source, cross-language, high-performance ELT (Extract-Load-Transform) framework powered by Apache Arrow. It is extremely fast and easy to run both locally and in the cloud (either via cloud.cloudquery.io or self-hosted), as it has a CLI-first design, is shipped as a single binary, and doesn’t need any additional services or UI to run.
What is Airbyte? #
Airbyte is an open source data-integration solution. Airbyte both has its own Python SDK to develop connectors as well as a UI and orchestrator to run connectors.
Comparison Overview #
| CloudQuery | Airbyte | |
|---|---|---|
| Architecture | Pluggable Architecture powered by gRPC and Apache Arrow. CLI-first and shipped as a single binary that can be run anywhere. | To run Airbyte, you need to deploy the whole full-stack solution, which includes 14 services and docker requirements. |
| Custom Source or Destination Development | Any Language (Golang, Python, Javascript, Java). More coming | Python and a custom No/Low-Code YAML-based DSL. |
| Sources | 97 (focused on cloud infrastructure connectors) | 350 (focused on marketing and sales connectors) |
| Destinations | All data warehouses, lakes, and databases. | All data warehouses, lakes, and databases. |
| Connector Quality | CloudQuery’s internal developers maintain all official connectors to ensure consistent quality | Highly varies, some connectors are not maintained. |
| Performance/Coverage | Focused on performance | Focused on more connectors |
| Orchestrator Integration | CloudQuery can run directly/embedded in Airflow, Dagster, Step Functions, Prefect, or any other orchestrator due to its light-weight, stand-alone cross-platform design. | Can Integrate with Orchestrators by the ELT workloads itself needs to run in an external Airbyte Instance. |
| License | • Framework is open source.• Plugins are closed-source commercial.• Pricing is the same for any use-case: internal, embedding, OEM, etc. | • ELV2 (Elastic License 2.0). • Cannot embed connectors without getting a special license. • Pricing is not available publicly |
| Pricing | • Volume-based pricing, varies depending on the connector • Flat fee yearly quotes are available based on average usage to protect against spikes.• Free quota is available for all plugins | • Volume-based pricing, varies depending on the connector |
Architecture and Deployment #
One key difference between the two vendors is architecture and deployment. CloudQuery is CLI first shipped as a single binary and with pluggable architecture where each plugin is a single binary as well. You run syncs by using configuration-as-code approach and define it in a simple YAML file. CloudQuery Cloud adds the UI layer and orchestration.
Airbyte is a UI-first approach where orchestration, configuration, and ELT engine are all coupled together.
Data sources and destination connectors #
Sources and destinations are the bread and butter of data integration solutions. With key differences, pros and cons, for each platform.
CloudQuery’s top connectors are high-performance connectors for AWS, GCP, and Azure that can sync all metadata and configuration from thousands of APIs concurrently to any destination. This massively helps platform engineers create an up-to-date infrastructure lake and drive use cases such as asset inventory, compliance, cost, and others.
Building custom connectors for CloudQuery is quick and can be done in under 15 minutes, with SDKs and tutorials available for the most popular (by usage) programming languages. Airbyte’s own documentation shows that doing the same would take hours and is only possible in either Python or their custom YAML-based DSL.
Performance #
CloudQuery official source and destination plugins are written in Golang and takes advantage of the excellent Golang Goroutines which can launch huge number of concurrent API calls at with minimal memory footprint. This gives a huge boost to complex connectors like AWS/GCP/Azure where thousands of APIs exist and performance and data freshness are key.
Pricing and Costs #
Both solutions use volume-based pricing that varies per container, but CloudQuery also offers a free quota for each connector and even offers annual flat-fee volume quotes to spread the cost of usage spikes over the year, giving you predictable monthly costs.
Conclusion #
We’re obviously biased, but we think CloudQuery is the clear winner in flexibility, performance, and pricing.
At the time of writing, Airbyte does have more connectors, but building new or custom connectors to work with CloudQuery takes minutes - and you’re more likely to hit a source API limit before you get a performance bottleneck.