Cribl, the Data Engine for IT and security, is debuting its next evolution within Cribl Lake—the turnkey data lake that makes it easy and economical to store, access, replay, and analyze data—with the launch of Cribl Lakehouse. Purpose-built for the dynamic, unpredictable nature of telemetry data, Cribl Lakehouse further centralizes data by enabling the storage of massive quantities of telemetry data, paired with real-time high-performance dashboards and analytics—without needing data engineering expertise.
IT and security teams are burdened with an overwhelming amount of telemetry data, including logs, metrics, and traces. Since this data is only valuable in the case of an incident or investigation, storing telemetry data becomes an increasingly wasteful—and costly—venture.
This is only further compounded by the present limitations of traditional lakehouses, which are fundamentally built for structured data. Meaning, these lakehouses often necessitate users to manually define schemas, have a robust understanding of SQL, and be capable of building parsers to make telemetry data usable at all, according to Cribl.
Cribl Lakehouse addresses these inefficiencies with real-time visibility, instant access to any stored data, and the ability to compose, manage, and query highly distributed datasets across regions, all within one unified, intuitive interface, according to the company. This evolution of Cribl Lake eradicates the rampant complexities of schema management and manual data transformation, all while forwarding ultra-elastic scalability, federated query capabilities with fine-grained RBAC (role-based access control), and a fully unified management experience regardless of data set diversity or geographic location.
“The idea of [Cribl] Lakehouse is it's going to be a massively distributed system where I can have my ‘right now’ data and right where I need it, so that it's going to be really fast, and then I can tear my other data off into different places, and then also scale it to my enterprise,” said Ed Bailey, senior technical evangelist, Cribl. “We constantly run into enterprises that have tens of, if not hundreds of teams that need access to data, they need RBAC, and they're global. [That’s what] Lakehouse is going to give us, a massively distributed way to have access.”
Cribl Lakehouse represents the next-gen evolution of lakehouse architectures, acting as a cloud-native solution with composable management, self-service access, and elastic resource consumption, according to the company. Offering a unified experience across all lakes and queries paired with schema-agnostic, no-code data management, Cribl makes managing telemetry data—and beyond—intuitive, efficient, and effective. Some of its key capabilities include:
- Federated, distributed data management that enables users to manage a single lake or multiple lakehouses across regions, preventing query interference, improving security, and driving granular RBAC by allowing worklows to be isolated.
- Intuitive, schema-agnostic, no-code data management that rivals traditional lakehosue architectures. Cribl Lakehouse automatically structures telemetry data for exploration and analysis, eliminating the need for complex SQL queries, custom parsers, or expensive ETL pipelines.
- Composable, cloud-native security by dynamically provisioning resources and keeping lakehouses close to data egress points, yet with a centralized control plane, ultimately helping to keep costs low, improve security, and optimize performance.
- Fully managed data experience by removing the need for robust database expertise, including that for time series databases (TSDB), columnar acceleration, or cloud data warehouses. Cribl intelligently routes and stores data in the optimal format, further helping to reduce costs by 50% compared to traditional solutions—all while driving seamless search and retrieval.
- Automated, tiered storage for cost optimization, defined by the user based on access frequency and retention needs.
- Augment existing tools by decoupling retention from systems of analysis, tiering used data from the system of analysis to free up capacity, and ingesting data that is needed but cannot be consumed into the existing system of analysis due to capacity constraints.
“Today's organizations need more than just another lakehouse. They need a flexible, highly scalable solution designed for the incredible volume, variety, and unique varying value of telemetry data,” said Clint Sharp, CEO and co-founder at Cribl. “Cribl Lakehouse allows customers to manage one or many lakes with ease, isolate workloads for performance and security, and dynamically accelerate queries across highly distributed datasets. By automating tiered storage and eliminating traditional complexity, Cribl gives customers the power to unlock full-fidelity data insights at a fraction of the cost.”
To learn more about Cribl Lakehouse, please visit https://cribl.io/.