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Power Law company profile

Hydrolix

Other B2B Software · Portland, United States · Founded 2018

Hydrolix, Inc. operates as a streaming data lake platform engineered to manage and analyze substantial volumes of log data with a focus on altering the cost structure of big data. The company was established in 2018 by CEO Marty Kagan and CTO Hasan Alayli, both of whom possess extensive backgrounds in the tech industry, including tenures at Cisco and Akamai. Their journey began at Cedexis, a CDN observability company co-founded by Kagan, where they experienced firsthand the prohibitive costs associated with storing massive datasets, a problem that became the foundational mission for Hydrolix. Kagan previously co-founded and served as an executive at several tech firms, including Cedexis which was acquired by Citrix, while Alayli has a background as a principal software engineer at Splunk. The company's core offering is a cloud-native platform that combines real-time stream processing, indexed search, and decoupled storage to handle terabyte-scale, append-only data. This architecture is designed to provide high-performance queries on large datasets without the typical high costs, addressing the trade-offs between data retention, query performance, and infrastructure expense. Hydrolix's business model targets enterprises with significant data logging requirements across various sectors such as media, e-commerce, and finance. Clients like Volkswagen, Navy Federal Credit Union, and those involved with the Paris Olympics use the platform for security threat detection, system debugging, and monitoring live events. A significant component of their go-to-market strategy involves the "Powered by Hydrolix" partner program, where the company builds and manages white-label observability solutions for partners, operating on a revenue-sharing model. A key partnership with Akamai resulted in the TrafficPeak observability solution, which has seen substantial customer growth. The Hydrolix platform is distinguished by its ability to ingest high-volume data streams from sources like Kafka and AWS Kinesis, applying real-time transformations and indexing. It utilizes a stateless Kubernetes-native architecture, allowing for the independent scaling of ingest, query, and storage components, which optimizes resource use. A core feature is its high-density compression and decoupled storage, which allows all data to remain 'hot' and queryable for extended periods—often over a year—without needing to tier data into warm or cold storage. This approach significantly reduces storage costs while maintaining sub-second query performance through massively parallel processing and per-column indexing. The platform supports standard query interfaces like SQL and integrates with popular visualization tools such as Grafana, Looker, and Superset, as well as offering connectors for systems like Spark and Splunk. Keywords: streaming data lake, log data management, big data economics, data observability, real-time analytics, high-volume data, data retention, query performance, cloud data platform, CDN observability, SIEM, AdTech analytics, data compression, decoupled storage, Kubernetes architecture, log analytics, Marty Kagan, Hasan Alayli, TrafficPeak, Akamai partner