Redis Labs Gets USD60 Million In Series E Funding Round For Database Platform

Big Data News

Redis_Labs-Gets-USD60-Million-In-Series-E-Funding-Round-For-Database-Platform Redis Labs Gets USD60 Million In Series E Funding Round For Database PlatformRedis Labs, the provider of a database management system, has raised USD60 million in Series E funding round to accelerate the delivery of the most efficient database to the world. The funding was led by Francisco Partners, a leading private equity firm. With this funding round, Redis Labs’ valuation has now reached USD146 million.

Redis Labs Co-founder and CEO Ofer Bengal said that this funding allows his company to stimulate their strategy to deliver the fastest and most efficient database to the world and allow immediate experiences for any modern application. Based in California, Redis labs now intended to speed up global go-to-market execution with the new funds and invest further in the Redis community. It further strives to keep its leadership to deliver the highest performing and most efficient database platform for modern applications. Other existing investors who invested in Redis Labs including Goldman Sachs Private Capital Investing, Viola Ventures, Bain Capital Ventures, and Dell Technologies Capital also participated in the funding round. Moreover, Francisco Partners’ CIO, David Golob will be joining as Board of Directors in Redis Labs, along with operating partner Eran Gorev who will be joining the team as a board observer, as a part of the new investment.

Founded in 8 years back in 2011 by its active CEO Ofer Bengal and CTO Yiftach Shoolman, Redis Labs is the world’s most popular in-memory database. It is also a commercial provider of Redis Enterprise, the world’s fastest database which utilizes the modern in-memory technologies such as NVMe (non-volatile memory express) and Persistent Memory. That allows the company to provide cost-effective deployment over compound Public Clouds and on0premise data centers. Unlike others, Redis Enterprise also comes with various data modeling methods like Streams, Graph, Document and Machine Learning, with a real-time search engine.