Company Profile: WekaIO

Company
WekaIO, Inc.
 
Location
HQs in San Jose, CA; engineering in Tel Aviv, Israel
 
Date founded
2013
 
Financial funding
$10 million in series A, $37 million in series B
 
Revenue
Estimated revenue under $1 million according to Owler
 
Co-founders

Liran Zvibel, CEO, guides long term vision and strategy. Prior to creating WekaIO, he ran engineering at a social start-up and Fortune 100 organizations including Fusic, where he managed product definition, design and development for a portfolio of rich social media applications. He also help principal architectural responsibilities for the hardware platform, clustering infrastructure and overall systems integration for XIV Storage System, acquired by IBM in 2007.

Dr. Omri Palmon, COO is a technology veteran for more than 30 years, brings his background in software development, research and product management to WekaIO. Previously he was VP marketing and product for XIV, a storage start-up, until its acquisition by IBM. Later he served as part of the IBM/XIV team until it reached half a billion dollars in sales. Before that, he held various technical and product-centric positions in telecommunications and embedded software development.

Maor Ben-Dayan, chief architect, brings a ranging skillset to the opportunities facing the company, skills won over nearly 20 years of technical experience in start-up and large corporate environments. As project lead for IBM’s XIV Storage System, he led a team of engineers developing future capabilities for the IBM XIV Storage platform. He also led development of collision avoidance technology at segment leader Mobileye and led a team developing Unix kernel code through all stages of development from requirements through research, development and testing under severe schedule pressure and high quality standards for the Israeli Defense Forces.
 
Number of employees
60
 
Technology
WekaIO Matrix is a fast shared parallel file system that leapfrogs legacy storage infrastructures by delivering simplicity, scale, and faster performance for a fraction of the cost of NAS. In the cloud or on-premises, WekaIO’s NVMe-native high-performance software-defined storage solution removes the barriers between the data and the compute layer, thus accelerating AI, machine learning, genomics, research, and analytics workloads.

Products description
Matrix software-defined storage is an NVMe-native, shared file system that runs on commodity servers or the AWS Cloud, delivering high bandwidth, low latency performance to any IB or Ethernet enabled GPU or CPU based cluster. Integrated tiering automatically and transparently migrates cold data to any S3 or Swift compatible private cloud for low cost and limitless scale. A dedicated storage server deployment is when you want to maintain separate storage and compute infrastructure for isolation or large capacity scaling.
 
The POSIX compliant file system runs more efficiently than NFS and leverages a customized protocol to deliver file based semantics. As a result, Matrix exceeds NFS performance in a sharable file system solution.
 
Matrix software can be deployed alongside other applications on existing GPU or CPU based server infrastructure presenting a POSIX compliant file namespace. It shares the existing Ethernet or IB infrastructure and provides low latency access to data. Integrated tiering automatically and transparently migrates cold data to any S3 or Swift compatible private cloud for low cost and limitless scale.
 
Whether applications run on-premises for performance, in a virtual environment for ease of deployment and resiliency, or entirely in the cloud for on-demand scalability, Matrix is a parallel, scalable file storage solution that delivers high performance to applications based on performance, scale, and economics.
 
Released date
June 2017
 
Partners
AWS, Dasher Technologies, Cambridge Computer, HPE, Nvidia, Mellanox Technologies, Intel, Google, Western Digital, Bodega, Cycle Computing, Dell, Supermicro, ASHG, BioCom, Emulex, NextGen, Cloudian, Qlogic, Scality, SERRO
 
Distributors and OEMs
HPE, AWS, Supermicro
 
Number of customers
20
 
Main customers
TGEN, SDSC, TuSimple, TRE Altamira
 
Applications
AI, machine learning, genomics, geospatial, post-production in media and entertainment, research, deep learning, quantitative analysis in banking and finance, and analytics workloads
 
Target market
AI/machine learning/analytics, HPC, life sciences, manufacturing, media and entertainment, banking and finance
 
Competitors
Include Lustre, GPFS, legacy NAS manufacturers