Ascend Debuts Structured Data Lake for Unified and Optimized Access to the Entire Data LifecycleIntelligent data storage layer managed by Ascend now accessible to external processing engines, notebooks, and more to extend usability across the ecosystem PALO ALTO, Calif. – Oct. 1, 2019 – Ascend, provider of the world’s first Autonomous Dataflow Service, today announced the general availability of its Structured Data Lake, allowing users to directly connect their existing data processing engines, notebooks, and BI tools to Ascend’s optimized data management system. For the first time, data scientists, architects, and engineers can build on top of a common data lake that automatically ensures data integrity, tracks data lineage, and optimizes performance. With the Ascend Dataflow Control Plane intelligently managing data storage across the data lifecycle, the Structured Data Lake delivers faster time-to-value for users across the enterprise and decreases overall data management costs. “We’re excited to extend the value of Ascend to an even larger user base,” said Sean Knapp, founder and CEO of Ascend. “The release of the Structured Data Lake is a huge step forward for accelerating the data development lifecycle. Teams can not only access more data than ever before, but can do so with confidence and security at any stage of development. And, with easy integration into the broader ecosystem, we are eliminating siloed access based on preferred tools or skills.” Backing Ascend’s Autonomous Dataflow Service is a highly optimized data store that is managed by Ascend’s Dataflow Control Plane, resulting in the first data lake that understands and reacts to the pipelines running against it. This intelligent data management is what unlocked Queryable Dataflows–bringing the interactivity of data warehouses to the scale of pipelines–and now extends the traditional data lake architectures with structured, secure, and optimized access to data flowing across the enterprise. With Ascend’s Structured Data Lake, all managed data is unified and dynamically synchronized with the pipelines that operate on it, making even mid-pipeline data sets available to existing processing engines such as external Apache Spark, Presto, or Apache Hadoop, as well as to familiar tools such as Jupyter and Zeppelin notebooks, all with no additional code or management complexity. The automated and intelligent management of Ascend’s Structured Data Lake introduces a number of capabilities never before possible from large-scale data management architectures, including:
- Trusted Data Integrity: The Structured Data Lake manages all data and updates as they happen with guaranteed data accuracy, automatic lineage tracking, and dependency management. It also supports atomic updates at scale and intelligent partitioning for safe and optimized access.
- Deduplication of Redundant Storage and Operations: As a unified storage layer, the Structured Data Lake has full visibility into every operation and data set being developed against it. From this, it ensures that no duplicate operations or data sets occur, and has the intelligence to materialize correct data sets as needed. This results in decreased storage costs as well as improved performance for repeat queries and operations.
- Automated Storage Maintenance: With comprehensive management of all data down to fine-grained partitions, the Structured Data Lake can automate some of the more tedious aspects of storage such as garbage collection based on active development, and intelligent backfilling with minimal reprocessing.