Real-time indexing database vendor Rockset said Tuesday it raised $40 million in a Series B round of funding.
Led by Sequoia and including participation from Greylock, the new round brings funding to date for Rockset at $61.5 million. Alongside the new financing, the vendor, based in San Mateo, Calif., expanded its database delivery options, adding the ability for organizations to deploy the real-time indexing database inside of an AWS Virtual Private Cloud.
Rockset is among the better-known vendors of real-time indexing databases, one of the foundational technologies for quick data access, the ability to rapidly ingest and index data so that it can be queried and used by applications.
Rockset was founded in 2016 and has its roots in the open source RocksDB key-value store project created at Facebook. Rockset has grown steadily, adding new capabilities including Query Lambdas in March 2020 and improved scalability in July.
In this Q&A, Venkat Venkataramani, CEO and co-founder of Rockset, discusses the need for real-time database technology and where the company is headed.
Why are you raising a Series A now?
Venkat Venkataramani: This was a preemptive round. We were not actually looking to raise at this point, because we still have enough gas in the tank to keep going.
Things are really picking up for our business and I think this is the time to really hit the gas pedal. We’re still a relatively small team, and we want to grow on the go-to-market side for sales and marketing and also on the product side with product management and engineering. So I think this is a great time to secure the funds and start growing the company to be able to handle more and more customers.
For years, every application would just start with a single simple transactional database. Modern data applications are asked to scale to much higher data volumes than ever before without compromising query speed. The combination of the speed and scale that modern applications demand is really the big driving force for a real- time indexing cloud database like Rockset.
What has been the impact of the COVID-19 pandemic on your business?
Venkataramani: I think in the pandemic, I feel like everybody has to run twice as fast to continue to grow at the same pace. Organizations are trying to do a lot more with the existing staff.
Venkat VenkataramaniCEO and co-founder, Rockset
The single biggest kind of customer feedback that we get is that we help to enable faster time to market in terms of building an application, scaling it and going live with it.
For Rockset itself, we had a remote working culture before COVID, but it wasn’t like what we have now. I think it definitely took us a couple of months to adapt to the new normal. Now I’m very happy to say I think we’re just as productive as we ever were, maybe even marginally more productive than before.
How have Rockset and real-time database indexing changed since you founded the company in 2016?
Venkataramani: The whole movement from batch to real time is picking up more steam. Real time used to be this kind of fringe thing that only bleeding edge companies had.
There is what we call data latency, which is how quickly data becomes actionable and then there’s also query latency, which is about how fast you can get answers. We have really seen the movement from batch to real time accelerating to support both data and query latency.
The adoption and massive growth of platforms like Apache Kafka means that enterprises are accumulating more real-time data. Acquiring data in real time only solves half of the problem; you still have to put the data to work and make better operational decisions on the ground using all the real-time data.
What’s next for Rockset and its real-time indexing database capabilities?
Venkataramani: As a company, we going to continue to hire staff as we’re actively recruiting and trying to grow every function within the company.
We want to definitely build more and more connectors to make it very easy for people to continue to onboard data no matter where it is. We also want to make it easier to build any type data application no matter where the data lives.
Editor’s note: This interview has been edited for clarity and conciseness.