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Company Overview: WekaIO

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Company Overview: WekaIO

Innovation leader in high-performance, scalable file storage for data-intensive applications.

· Big Data Zone ·
Free Resource

I had the opportunity to meet Liran Zvibel, Co-founder and CEO, Barbara Murphy, V.P. of Marketing, and Shimon Ben-David, Director of Sales Engineering at WekaIO, the fourth company in IT Press Tour #31.

According to Liran, WekaIO is 10X faster than other all-flash storage solutions. The fastest, most scalable file system, on-premises and in the public cloud, as well as the fastest growing storage company.

Data storage has a sad history of compromise. DAS (EC2) provides great performance, with wasted capacity, inability to back up, share data, and scale. SAN (Amazon EBS) provides good performance, more efficient storage, backup, inability to share data, and it's complex to manage. NAS (Amazon EFS) has okay performance, more efficient storage, it's easy to manage and share data, but it doesn't scale. OBJ (Amazon S3) performs poorly, has no file system, but it has massive scalability, and it's easy to share data.

WekaIO went back and fixed storage. It's faster than NVMe DAS, provides complete data shareability, POSIX semantics, object storage scaling, it's simple to manage, mixed workloads actually work workload migration with hybrid cloud, and cloud-native, cloud liquidity. The first true “fits all storage.”

They are going after applications where they can have significantly higher performance. WekaIO has redone the way file systems are handled with infrastructures and algorithms and offers performance at any scale to take advantage of a 10X increase in computing power. Networking = 10X the data into a single GPU server. Storage scaling is able to manage the 50X scale of data.

WekaIO solves the performance challenge with:

  • A parallel file system written for NVMe, and modern networks.
  • Rearchitected for the highest performance (IOPS/throughput) and lowest latency.
  • A file system as scalable as object storage.
  • Fully featured for technical compute in the enterprise, on premises, or the cloud.
Topics:
big data ,data storage ,big data storage ,big data sets

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