Compare - Onehouse VS Fabra
Here’s the difference between Onehouse and Fabra. The comparison is based on pricing, deployment, business model, and other important factors.
About Onehouse
Onehouse delivers a new bedrock for your data, through a cloud-native managed lakehouse service built on Apache Hudi, which was created by the founding team while they were at Uber. Onehouse makes it possible to blend the ease of use of a warehouse with the scale of a data lake, by offering a seamless experience for engineers to get their data lakes up and running.
About Fabra
"Fabra helps B2B SaaS companies ingest external user data into their application. Our vision is for every SaaS application to natively integrate with the Modern Data Stack, empowering their users to seamlessly adopt data-driven processes. After building SaaS products for years, we know that working with external data can be a nightmare. And it's only getting worse, with an ever-growing number of data sources and infinite formats, quirks, and data types. With Fabra, we're making it possible for applications to define their expected data once, and receive it in that format every time, regardless of where it's coming from or how it's shaped. To do so, we're building a powerful toolbox of automatic validation, cleanup, and transformation functions that enable users to easily onboard their data into your system. A core value at Fabra is providing the best developer experience. First of all, we make integrating with Fabra effortless regardless of what your architecture looks like. Our system can sync data directly into your application database, send data to a webhook, and more. You can also use our pre-built and customizable UI components to offer data onboarding to your users immediately, or build your UI entirely from scratch by calling our APIs. Once you're integrated, we provide maximum visibility and control over the data ingestion process. You can setup notifications for any failures and leverage a variety of tools to diagnose and solve issues."
Comparison Table
| Overview | ||
|---|---|---|
| Categories | Data Lakes | ETL Tools |
| Stage | Early Stage | Early Stage |
| Target Segment | SMBs, Mid-size, Enterprise | Enterprise, SMB's |
| Deployment | Open source | Open Source |
| Business Model | Commercial | Open Source |
| Pricing | Conatct Sales | Freemium |
| Location | Menlo Park, California | San Francisco, CA |
| Companies using it | ||
| Contact info |
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