Software December 17, 2020
Digitization has created a data tsunami and the need for data driven insights has grown at an unprecedented pace. Businesses thriving in the intelligence economy are seeking out solutions that provide real-time continuous data analytics as legacy solutions are not designed to address the complexity of modern data storage and new requirements of the intelligence economy. While data analytics is a cornerstone of various business operations, bearing the cost of storing data indefinitely in the cloud is prohibitively expensive because existing solutions force you to transport and transform data multiple times, while also storing it in multiple locations. As a result, businesses are sacrificing key visibility into their infrastructure which is in parallel getting more complex by the day.
ChaosSearch’s novel technology mirrors the operational and economic models of cloud computing. ChaosSearch’s proprietary index compression technology can significantly reduce the size of underlying data while retaining the ability to fully index it, resulting in considerably less storage and compute resources utilized. While the applications of this technology are numerous, like all of the best companies we have had the benefit of working with over the years, they are remaining laser focused - they are currently tackling log management, a key first application in the larger analytics market. ChaosSearch enables organizations to increase their log coverage and retention with up to 80% lower cost than traditional solutions.
Additionally, like with the most well-designed products, ChaosSearch is deadly simple to adopt – it preserves existing workflows by integrating with open-source visualization tools like Kibana, allowing customers to get up and running instantly. Teams at Hubspot, Klarna, Blackboard and Alert Logic are using ChaosSearch to scale their log analytics workflows at disruptive economics. Hubspot not only saves millions annually with ChaosSearch, but also ingests 10x the log volume relative to other solutions.
Stripes Leads ChaosSearch’s $40M Series B Financing
We are excited to announce that we are starting a partnership with ChaosSearch by leading a $40 million Series B investment. At Stripes, we have long been committed to backing founders building exceptional products. After hearing companies discuss their frustrations with existing solutions, ChaosSearch’s promise of delivering a better, simpler, and more cost-effective solution felt unbelievable. As we spoke to multiple customers and they confirmed that they were in fact delivering on this promise and more, we knew they had built a special product that was easy to adopt, powerful and revolutionized the economic fundamentals of machine data analytics. Additionally, ChaosSearch is a great example of our core thesis on the data driven enterprise, as evidenced with our investments in Dataiku, Hyperscience, and Fullstory, among others. Despite commercializing their product less than a year ago, ChaosSearch has achieved incredible product market fit and has quickly become instrumental to their customers’ infrastructure stack.
The ChaosSearch team is led by exceptional leaders who possess both experience and integrity. Both CEO Ed Walsh and Founder and CTO Thomas Hazel are phenomenal entrepreneurs, who immediately impressed us by their astute vision of achieving the true promise of delivering insights at scale. Thomas is an inventor who has nearly 30 years of engineering experience - prior to founding ChaosSearch, Thomas was founder and CTO at Deep Software Foundation, Chief Architect at Akiban Technologies, and creator of Oracle’s virtualization management framework. Ed is an outstanding leader who previously led IBM’s $6 billion storage division. Before that, Ed ran multiple startups as CEO in the data storage space that he led to successful acquisitions by some of the most storied names in enterprise technology, including IBM, Oracle, and EMC.
We are honored to be part of ChaosSearch’s journey as they use their groundbreaking technology to challenge the status-quo of data access, performance, and scalability.