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UNIVERSAL DATA STORAGE
All-Flash Data Lakes at Archive Economics
As the modern data science stack continues to evolve, the motivations that previously drove organizations to adopt Direct Attached Storage (DAS) systems such as Hadoop Distributed File Systems (HDFS) have evolved.
Enterprises continue to embrace real-time computing tools such as Apache Spark, Trino, and Elasticsearch, shifting away from batch-oriented tools of the Hadoop era.
To that effect, storage must be now architected for delivering real-time performance for any query load, while accommodating the continuous evolution of data science toolsets and the inevitable data growth.
VAST DATA UNIVERSAL STORAGE
Flexible and Future Proof
But most file and object storage systems (new and legacy) fail to scale performance affordably for your current applications and are not architected to scale beyond a few petabytes.
VAST data architecture breaks these trade-offs with its unique Disaggregated and Shared-Everything (DASE) architecture and provides a highly scalable and affordable all-flash, file, and object platform that allows you to run petabyte and exabyte scale analysis at less than half of the cost of traditional all-flash solutions while being many times faster.
LIMITLESS SCALE
A Smarter Way to Power Your Query Engines
The proliferation of ad hoc and interactive query engines means customers need predictable, real-time performance for supporting thousands of queries simultaneously. Query engines need to be able to randomly read across massive data sets, which imposes significant I/O requirements, making flash infrastructure critical.
This combined with the surge in Python programming and GPU-accelerated computing, means customers need to evolve beyond HDFS and traditional object storage solutions. VAST Data’s disaggregated approach to data lake storage delivers a unified, flash-optimized platform that eliminates the need for multiple systems to store different types of data, resulting in a simple & scalable environment for all your data.
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