Virtualization Startup Varada Streamlines Data Ops
Varada, a data virtualization startup targeting big data query acceleration, announced a $12 million funding round this week as it ramps up its “zero data-ops” platform designed to prioritize analytics workloads via proprietary indexing technology
The Series A round announced on Tuesday (Sept. 15) was led by MizMaa Ventures, and early stage investors in Israeli technology startups. Gefen Capital joined seed investors F2 Venture Capital, Lightspeed and StageOne Ventures.
Tel Aviv-based Varada is readying a data virtualization platform for accelerating big data workloads via its patented indexing technology. The platform is intended to help prioritized workloads to “balance performance and cost.”
Varada’s value proposition aims to leverage data virtualization as a way to query data from disparate sources from a “single endpoint,” thereby eliminating IT operations such as configuration and modeling. Like similar approaches, the data virtualization scheme seeks to reduce data movement and, with it, reduce latency.
Other data engineering schemes have added data virtualization layers as a way to accelerate data analytics workloads regardless of where they reside.
The startup is also targeting market leader Snowflake, which recently introduced a data cloud intended as a portal where organizations can execute data-oriented tasks beyond data warehousing and SQL analytics, including machine learning, data engineering and monetizing third-party data.
Varada stresses its approach, unlike Snowflake’s, does not require users to configure their data into a proprietary format.
It also seeks to address scaling limits that have slowed data virtualization efforts and onerous data operations tasks required to work out the infrastructure kinks that hamper performance. “This round of Series A funding will accelerate the progress of our solution and allow us to quickly scale our plans to deliver the new standard for data virtualization,” said Varada CEO Eran Vanounou.
The startup’s proprietary indexing technology uses machine learning to speed priority queries by eliminating operations overhead required for query processing and data maintenance. Indexes are managed via Varada’s “cost-based” optimizer. The data virtualization framework is designed to identify which queries to accelerate and which data access indexes to maintain.
Varada’s investors tout the data virtualization startup as the successor to current DevOps teams that have accelerated the delivery of data-driven analytics workloads.
Varada was founded in 2017 by David Krakov, Roman Vainbrand and Tal Ben Moshe, veterans of the Dell EMC’s XtremIO team. According to the web site Crunchbase.com, it has so far raised $22 million in venture funding.
The startup is also active in promoting the open source SQL query engine, PrestoDB and PrestoSQL.