Enabling the Customer Data Stack: RudderStack Series B Funding
Today, I’m thrilled to announce RudderStack’s $56 million Series B funding led by Insight Ventures with continued support from Kleiner Perkins and S28 Capital. This brings our total funding to $82 million. Our Series B is a big step forward in helping our customers build the best data stacks possible.
In 2019, I co-founded RudderStack with the goal to help data engineers build the infrastructure required to help their businesses understand their users and serve their needs. I was inspired by my experience at my previous company where I spent a year building customer data pipelines. In the process, I learned about the data management challenges that engineering teams face as they strive to collect and process customer data at enterprise scale. This funding round is a testament to the progress we have made in addressing these challenges for our customers.
With this funding round, we intend to accelerate investments in our product to enable engineers everywhere to build future-proof customer data infrastructure.
I am proud of what this team has accomplished in just a few short years and am looking forward to what the future holds.
Read the TechCrunch article from Frederic Lardinois featuring our Series B to learn more.
Published:
February 2, 2022
Data without compromise: The RudderStack story
Learn about how RudderStack started and how it has evolved into a best-in-class data infrastructure solution to help businesses move their customer data with full control and safety.
Announcing RudderStack Data Apps, powered by Snowflake: Ship high ROI data projects faster
Run RudderStack Data Apps on top of your Customer 360, and ship high-ROI data projects in days, not months. Configure and run accurate attribution and propensity models and enable real-time personalization. All without writing complex SQL or Python.
Feature launch: Append and table skipping for warehouse FinOps
To help you turn your customer data into competitive advantage while optimizing warehouse spend you can now reduce compute time and costs by ingesting events via append and skip compute-intensive tables as requirements permit.
