Bobsled, a startup building a cloud-to-cloud data exchange platform, has announced that it has secured a $17 million Series A funding round co-led by greycroft y Madrona Venture Group. This round follows a $7 million seed round led by .406 ventures. In this latest round, Bobsled's valuation was $87 million.
Before founding Bobsled in late 2021, the company's CEO and co-founder, Jake Graham, was a Senior Product Manager at Microsoft Azure, working on Azure Data Exchange. Graham, who has also previously worked at Neo4j and Intel, believes that data sharing is going to fundamentally change the analytics landscape.
“It's the next evolution of how businesses access the data they need to do machine learning analytics, data science, etc.,” he says. “I've been working in the data infrastructure space for a decade, and accepting that APIs and SFTP were the way data moved was something I accepted. It was not until I began to delve into the subject that I said to myself: it should not be like this. This doesn't make much sense. They are built for an older data paradigm.”
Graham also believes that it is important that the clouds and the data platform create the building blocks of what a native exchange protocol should be.
“If you believe that data sharing is the way the world is going to go and that there is going to be much more active collaboration on data between source and destination, there needs to be something that brings all these different platforms together. Because there's no proper cloud, there's no proper data store, there's no proper layer of the stack for the data exchange to happen,” he said.
Bobsled, unsurprisingly, he believes that it may be this neural third-party data sharing platform that allows companies to connect their various data sources in a more native way. The service uses the exchange protocol of each platform, connects the different sources and helps companies to prepare the data sets for consultation.
Some of the common use cases here are SaaS applications that may want to share AWS S3 application data on a customer's Azure storage, for example, or a data team that wants to move sales data from Azure to S3 for its analysis.
Obviously, there are other companies that are focused on this type of data transfer and data transformation space. But Graham believes that with these ELT platforms like Fivetran, the consumer still has too much work to do. “A lot of what ELT platforms do should be done by the source of the data,” he says. "So we're leaving a lot of that. If you separate the letters, you extract: you are doing it because it is not shared with you. Carry? The same. If you're getting a part inside Databricks, you're not loading into anything." Regarding data transformation, he noted that most of the time, the data is in a transactional data model that needs to be formatted for analysis and the source must transform that data – although he believes that transforming data from multiple data sources to match a given schema is always going to be up to the consumer.
“I wouldn't call us an ELT product directly yet because we're quite different, but I think it's the closest thing to the category we're building. It's just a different user," Graham explained.
The company plans to use the new funding to develop its platform, especially with a focus on compatibility with more data sources (including old-school SFTP sources).
“The promise of AI only increases the urgency and priority for companies to unlock the value of their data,” says S. Somasegar, CEO of Madrona. “Even within companies and between partners, that data is now spread across platforms that are not designed to work together. Bobsled's unique approach to sharing data between clouds will unlock the value of data that has been complex, slow and expensive to access until now."
