ChaosSearch provides a data platform that integrates with Databricks to enable scalable log analytics using native Elasticsearch query capabilities. The solution consolidates log and event data in a unified data lake, offering unlimited retention and reducing costs by 50-80% while eliminating the need for data movement or transformation.
Funding
$56M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
MCFounders
Product
Problem
Organizations struggle with the high costs and operational overhead of traditional log analytics solutions, especially when dealing with large volumes of data and long retention periods. Existing solutions often require complex data movement, transformation, and infrastructure management, leading to increased costs and resource constraints.
Solution
ChaosSearch provides a cloud data platform that enables organizations to perform log analytics at scale directly within their existing cloud object storage, such as Amazon S3 or Google Cloud Storage. By indexing data in place, ChaosSearch eliminates the need for data movement, transformation, and dedicated infrastructure, resulting in significant cost savings and reduced operational complexity. The platform offers native Elasticsearch API compatibility, allowing users to leverage existing tools and skills for search, SQL analytics, and machine learning. This approach enables organizations to retain and analyze vast amounts of historical log data for improved troubleshooting, security analysis, and business insights.
Target Audience
The primary target audience includes DevOps engineers, security analysts, and IT operations teams who need to analyze large volumes of log data for troubleshooting, security monitoring, and performance optimization.
Features
- Direct indexing of data within Amazon S3 and Google Cloud Storage, eliminating data movement and transformation
- Elasticsearch API compatibility for seamless integration with existing tools like Kibana
- Support for SQL analytics and machine learning on log data
- Scalable and cost-effective long-term data retention
- Role-based access control (RBAC) for secure data access
- Automated log collection and centralization
- Integration with SIEM solutions for threat detection
- Ability to create Kibana dashboards and visualizations