Qbeast Raises €2.5m to Make Data Lakes Fast and Easy to Use

Today we are proud to announce our seed round of €2.5m led by Elaia, with the participation of new investors Sabadell Venture Capital and Uber Founding CTO Oscar Salazar and existing investor Inveready. Previous investors include BStartup Banco Sabadell and business angels.The funding will allow us to accelerate go-to-market by filling key commercial positions and further investing in product development, technology, and partnerships.

Qbeast team

Faster, cheaper, and easier-to-use data lakes

Qbeast’s solution simplifies the work for engineers managing data lakes. Qbeast organizes all the companies’ data so that they can read it efficiently from any solution they prefer, making it way cheaper to use their favorite Business Intelligence tool or train their Machine Learning models at scale.

Cesare Cugnasco (CEO) explains:

Companies dealing with data have little choice: if they want to know what is happening in their business, they need to use a data warehouse. If they want to predict the future, optimize its processes, and use Machine Learning, they need a data lake. They end up using different technologies and needing different people, but also with double the cloud bill and double the time to develop, which is a huge problem. At Qbeast, we are going to change this by making the life of data teams easier and data tools more efficient.

Qbeast developed the most advanced open-source format for data lakes to power its solution. We are building a community around the open-source data lake format. The Engineering team is currently further integrating the format within the modern data infrastructure stack to appeal to even more companies regardless of their technology stack.

For one of the clients, Qbeast improved execution time in their data analytics by 68% with full precision and by up to 50 times using sampling, enabling faster analytics, cloud cost savings, and lower energy consumption. Qbeast has already signed paying clients, such as a Cybersecurity company. Furthermore, Qbeast collaborates with Preply to improve the efficiency of Machine Learning model training. Qbeast’s innovative solutions can be particularly interesting for Marketplaces, E-Commerce platforms, IoT, and companies from industries such as Advertising & Marketing, Manufacturing, Retail, and Financial Services.

Sébastien Lefebvre, Partner at Elaia:

We are proud to back Qbeast and their highly capable team anchored in advanced research. The founders are on a mission to reduce the friction that prevents hundreds of thousands of companies from efficiently leveraging data lakes because of their perceived complexity. There is a lot of value to be created by Qbeast and we can’t wait to start this journey together.

The trade-off between flexibility and efficiency in data analytics was already a pressing concern in the Barcelona Supercomputing Center when Cesare Cugnasco (CEO) started to design Qbeast in 2015, way ahead of the battle between Data Warehouse and Data Lake solutions.

In 2020, he gathered a team of 4 co-founders, Pol Santamaria, Paola Pardo, Clemens Jesche, and Nicolas Escartin, and it was the start of Qbeast. Today, Qbeast put together a team of 14 talents, 4 of whom joined since the closing of the round. The team combines skills in engineering and business and plans to grow further over the next year.

What we have achieved so far would not have been possible without our fantastic Qbeast community. Thanks to our partners, customers, investors, advisors, and team members for all of your contributions and support!