comparisons
CloudQuery vs Fivetran
Tim Armstrong •
CloudQuery vs Fivetran: A Comprehensive Comparison #
The landscape of data integration and movements constantly shifting. Choosing the right ELT tool depends on the requirements, needs, and resources available. This blog will compare the pros and cons of CloudQuery vs Fivetran to help you decide.
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), 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 Fivetran? #
Founded in 2012, Fivetran is one of the oldest and biggest data integration cloud platforms. It offers a generous, albeit technically limited, free tier. Unlike many of its competitors, Fivetran is closed-source and only has an on-prem solution for enterprise-tier customers.
Comparison Overview #
| CloudQuery | Fivetran | |
|---|---|---|
| Architecture | Pluggable Architecture powered by gRPC and Apache Arrow. CLI-first and shipped as a single binary that can be run anywhere. | Firetran is a closed-source hosted platform with a self-hosted option for enterprise customers. |
| Custom Source or Destination Development | Any Language (Golang, Python, Javascript, Java). More coming | Custom connectors are built as cloud functions via AWS Lambda, Azure Functions, or Google CloudFunctions. |
| Sources | 97 (focused on cloud infrastructure connectors) | 406+ pre-built connectors focussed on data movement and replication between platforms |
| Destinations | All data warehouses, lakes, and databases. | All major data warehouses, lakes, and databases. |
| Connector Quality | CloudQuery’s internal developers maintain all official connectors to ensure consistent quality | 297 connectors are considered “Lite” - meaning they only support a limited set of use cases |
| 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. | Fivetran operates as a hosted platform and doesn’t integrate with other orchestration solutions |
| License | • Framework is open source.• Plugins are closed-source commercial.• Pricing is the same for any use-case: internal, embedding, OEM, etc. | Proprietary licenses and EULAs |
| 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 on Monthly Active Rows• Free quota is available |
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.
Fivetran is a closed-source software-as-a-service platform, so you cannot modify or fix it yourself if something goes wrong.
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.
Fivetran has good coverage with a lot of connectors, but compared to CloudQuery, they are very slow, and building your own requires the use of function-as-a-service platforms, adding further costs.
Performance #
While CloudQuery has a competitive number of production-ready connectors (source plugins), it prioritizes performance first. This pays off in performance comparisons, where our users and customers have seen more than 50x speed improvements when switching to CloudQuery.
More on this coming soon!
Pricing and Costs #
Both solutions use volume-based pricing, 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, Fivetran does have more connectors, but building new or custom connectors to work with CloudQuery takes minutes - and with CloudQuery you’re more likely to hit a source API limit before you get a performance bottleneck.