Being able to analyze hundreds of terabytes to petabytes of log data is critical to keeping applications, IT systems, and cloud environments running. But conventional log and data analytics solutions—such as those built on open source toolsets like Elasticsearch – have fixed architectures that make it impossible to cost-effectively handle very large data volume and retain it for long periods. Legacy “big data” solutions like Hadoop are equally expensive and complex.
According to Thomas Hazel, Founder and CTO of ChaosSearch, “ChaosSearch 2.0 takes a completely different and entirely new approach. Built from the ground up to achieve the true promise of cloud data lakes, ChaosSearch makes it as easy for customers to get insights out of their lake as it is to dump data into it. While other solutions require DBAs and data engineers to set up new workloads, extract data from storage, manually transform it, and then load it into a vendor’s analytic database, ChaosSearch 2.0 customers simply stream any amount of data into their own Amazon S3 data lake, where our solution automatically transforms and analyzes it. Our distributed architecture and proprietary indexing and compression technologies enable businesses to gain new and better insights, quickly and at a fraction of the cost.”
Customers Agree
“With ChaosSearch, we’re able to process tens of terabytes a day of Cloudflare log data without worrying about performance or system failure,” said Stephen Salinas, Engineering Lead at Hubspot, whose sales and marketing SaaS platform is used by more than 73,400 customers.
“ChaosSearch powers our enterprise log analytics and is a critical piece of the infrastructure for processing tens of terabytes per day of our customers’ log data. We’ve been very pleased with the performance, reliability and cost of ChaosSearch. As Armor grows and evolves, we plan on expanding our use of ChaosSearch to other areas at Armor. We are very happy with them as a trusted partner,” said Josh Bosquez, CTO at Armor, a global cybersecurity company with more than 1,000 customers in 42 countries.
ChaosSearch 2.0 Advantages
○ New workloads within 5 minutes versus weeks and months
○ High performant/automated indexing within your cloud storage
○ Search Analytic API(s)/visualization directly from your cloud storage
○ Fully indexed data sources provide compression ratios upwards of 90%
○ Unlimited retention, driving insights not possible with other solutions
○ Zero system management: ChaosSearch 2.0 is a fully managed SaaS
○ Zero data movement or ETL: ChaosSearch 2.0’s in-place Chaos Refinery™
○ Chaos Refinery automates clean, prep, and transformation with virtual views
○ Up to 80% less expensive than other log analysis solutions, including ELK Stack implementations, due to breakthrough index technology and architecture
○ Scales from gigabytes to petabytes of data instantly, without cost or complexity
○ Zero vendor storage: Customers own their data, 100% within their own cloud storage
○ Fine grained Role-based Access Control (RBAC) across all data sources and users
About ChaosSearch
ChaosSearch delivers on the true promise of data lakes, instantly turning a company’s own cloud object storage into a hot, robust, streamlined data analytics engine, where it is as simple to generate insights from the lake as it is to dump data into it. Implemented today as a data lake engine for scalable log analysis on Amazon S3, ChaosSearch is an ELK-compatible, highly secure, fully managed service that scales to petabytes of data, quickly and at disruptively low cost. The privately held company is based in Boston, MA. For more information, visit ChaosSearch.io or follow on Twitter @ChaosSearch.