Unveiling Chaos LakeDB: The First Lake Database for Live Search+SQL+GenAI Analytics


ChaosSearch, a leader in data analytics, announced the release of Chaos LakeDB, the first and only data lake database designed to power live Search, SQL, and Generative Artificial Intelligence (GenAI) analytics. By integrating with Amazon Web Services’ (AWS) Amazon Simple Storage Service (Amazon S3), the preferred object store for millions of AWS customers of all sizes and industries, Chaos LakeDB helps merge the vast storage capabilities of data lakes with the accessibility of cloud databases. This fusion of lake and database capabilities eliminates the need for complex extract, transform, load (ETL) and extract, load, transform (ELT) processes, offering live analytics while ensuring enhanced cost efficiency and performance at scale—crucial for data-intensive analytics and AI applications. Chaos LakeDB is available as a Software as a Service (SaaS) data platform for enterprises and now as an embedded database for cloud platform providers. Prominent industry leaders such as Cisco and Equifax have already adopted Chaos LakeDB.

In the swiftly changing digital era, the ascent of Generative AI is not merely a passing phase but a necessity for businesses aiming to stay ahead. Yet, many are trapped in outdated data strategies and associated solutions, grappling with the nuances of LLM integration, like security, orchestration, and escalating costs for data access. When this is compounded with ever-increasing data volumes, laborious preparation, fragmented silos, and the taxing “integration overhead” from disparate systems, the picture is clear: legacy systems are hampering routine tasks, as well as groundbreaking innovation. In this new digital AI epoch, such inefficiencies are not just minor hitches—they directly jeopardize an organization’s market position. The solution? A revolutionary approach to truly unlock the potential of your data.

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Introducing Chaos LakeDB: A new data lake database solution from ChaosSearch. It transforms cloud object storage into a live Search+SQL+GenAI analytics database with unlimited hot data retention. This creates a unified data lake suitable for both operational and business use cases. This solution can result in savings of 50-80%, free up technical resources, and simplify your architecture.

Aggregate: Chaos LakeDB consolidates diverse data streams and formats into one cohesive data lake database. With its advanced Search + SQL and GenAI analytics, it caters to a wide spectrum of operational and business needs, providing a comprehensive platform for deriving insights from data.

Automate: Chaos LakeDB redefines data management by intuitively automating the data pipeline, schema management and the orchestration of workloads across a lake backbone. With its adaptive capabilities, it identifies and scales stream types and schemas, ensuring data remains up-to-date and relevant, eliminating the need for constant manual intervention.

Activate: With Chaos LakeDB, provides both real-time and historical insights at scale, integrating Search+SQL and GenAI across all functionalities. This ensures that every interaction with data becomes a source of actionable intelligence.

Industry leading customers, including Equifax and Cisco, rely on Chaos LakeDB to manage workloads across a unified lake backbone, eliminating the constraints observed in alternative solutions and achieving remarkable reductions in time, cost, and complexity. Chaos LakeDB is a holistic and unified solution that offers live analytics without the burdens of extremely labor-intensive processes and outdated systems. With Chaos LakeDB, businesses are leveraging their data to the fullest potential, which is important in an AI-centric world.

“With ChaosSearch, we no longer have to move or transform our data. We don’t have to think about how we’re going to use the data before we access it. It’s just there for us to query. That helps us deliver new opportunities to the business or discover usage patterns in our systems. Taking a piecemeal approach to data analytics got expensive quickly, and it became difficult to pull insights together to paint a broader picture that spanned knowledge silos. It’s a much more ubiquitous platform we can use to access data across disparate systems, at scale.” – Jeff Kinsherf, SVP, Engineering Services and SRE at Equifax.

SOURCE: Businesswire