M&A Deal Summary

StorCentric Acquires Violin Systems

On October 29, 2020, StorCentric acquired information technology company Violin Systems

Acquisition Highlights
  • This is StorCentric’s 2nd transaction in the Information Technology sector.
  • This is StorCentric’s 3rd transaction in the United States.
  • This is StorCentric’s 1st transaction in Colorado.

M&A Deal Summary

Date 2020-10-29
Target Violin Systems
Sector Information Technology
Buyer(s) StorCentric
Deal Type Add-on Acquisition

Target

Violin Systems

Colorado Springs, Colorado, United States
Violin Systems LLC provides extreme-performance enterprise storage for customers to maximize the value of their business-critical data. The company offers IOPs with the lowest latency plus extensive data services, including data protection, business continuity, and data reduction, Violin solutions enable businesses to improve their application performance and reliability while raising business service levels. Violin Systems was formed in 2005 and is based in Colorado Springs, Colorado.

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Buyer(S) 1

Buyer

StorCentric

Sunnyvale, California, United States

Category Company
Founded 2018
Sector Technology Hardware
DESCRIPTION

StorCentric, Inc. provides storage solutions for prosumers, SMBs and enterprise customers. StorCentric, Inc. was founded in 2018 and is based in Sunnyvale, California.


DEAL STATS #
Overall 3 of 3
Sector (Information Technology) 2 of 2
Type (Add-on Acquisition) 3 of 3
State (Colorado) 1 of 1
Country (United States) 3 of 3
Year (2020) 1 of 1
PREVIOUS DEAL
DATE TARGET DEAL TYPE VALUE
2019-07-02 Vexata

San Jose, California, United States

Vexata powers today’s demanding enterprise applications driving fast access to large datasets for workloads such as predictive analytics, IOT, and autonomous decisions. Based on patented active data architecture, Vexata delivers 10x performance and efficiency improvements at a fraction of the cost of existing all-flash storage solutions. The result is a transformative performance with breakthrough economics across numerous data-hungry applications at enterprise scale.

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