Daniel Buchuk
NOV 9, 2021
5 min read
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Rivery’s new plans and pay-as-you-go pricing removes the barriers that can make the purchasing process long and complex, giving a perfect solution to data and BI analysts that want to hit the ground running and need an end-to-end solution they can start using in minutes.

Connect all your data sources with pre-defined APIs, build, manage, and monitor data pipelines and workflow logic, without help from development teams or coding knowledge. Rivery’s Kits shortens the time to insight even more, by providing pre-built data pipelines and workflow templates, reducing the need for help from data engineers or architects.

Why self-service?

Whether you’re a data analyst at a large organization or building the DataOps infrastructure at a small startup, Rivery is now at your fingertips. The new self-service registration was created to bring unprecedented autonomy, agility, and accessibility.

1. Autonomy

Data analysts and engineers can autonomously create and manage complex data workflows. Not having to rely on external teams and developers empowers anyone to access data, deploy predefined data models, and autonomously create a DataOps ecosystem to deliver optimal business insights.

2. Agility

Anyone can access data and create insights from any source in just a few clicks, with out-of-the-box API connectors, and pre-engineered pipelines & workflows. Rivery’s no-code interface and orchestration features make it easy build and manage your pipelines in minutes,

No monthly fees, no minimum spend. Just pay as you go and enjoy Rivery in its entirety – from the simple API connectors, to pre-engineered ready-made data workflows that empower teams to gain access to insights faster than ever before.

3. Accessibility

Code-free and hassle-free, Rivery is designed to democratize access to data. A self-service approach takes this one step further, empowering anyone to try Rivery without any commitments. 

What’s more, anyone can browse through the growing repository of Kits – pre-defined data models that anyone can deploy without help from data engineers or developers. This means not just making any data source accessible, but also making any data model attainable. 

Minimize the firefighting.
Maximize ROI on pipelines.

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