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Tel Aviv-based Firebolt, a startup developing a cloud data warehouse for analytics, today closed a $37 million funding round. A spokesperson told VentureBeat the funds will be used to bolster Firebolt’s go-to-market efforts as it invests in product R&D.
The cloud data warehousing market is booming, with some analysts predicting the global market will reach $3.5 billion by 2025. But warehouses can become an outsized expense. Cool Data pegs the cost of a terabyte of storage and 100,000 queries per month at around $468,000, on average, accounting for total yearly cost for storage, software, and staff.
SiSense veterans Eldad Farkash and Saar Bitner cofounded Firebolt with the goal of improving the price-performance ratio of data warehousing. The company’s platform allows for the scaling up and down of compute nodes in a shared-nothing architecture while relying on Amazon Simple Storage Service (Amazon S3). (A shared-nothing architecture is a distributed computing architecture in which each update request is satisfied by a single node.) With Firebolt, customers can leverage data lakes and S3, working with data in common file formats to prep it for performant querying.
Firebolt combines technologies to deliver baseline query performance at terabyte (and even petabyte) scales. A columnar data structure enables faster analytics workloads, while vectorized processing and SIMD utilization supports high throughput at the processor level. Firebolt also boasts just-in-time query compilation using LLVM for hardware-optimized query plans and continuously aggregates indexes for speedy ingestion speeds and data updates.
Firebolt claims to be the first company to deliver a “sub-second” data analytics experience, regardless of the size and usage patterns of a customer’s data. In a recent benchmark, Farkash says the platform ingested 39 billion rows of data in 2.5 hours at a compute node costing $20 per hour. He compares this with the second-best result by “a well-known cloud data warehouse vendor,” which ingested the same data in six hours at $300 per hour. Moreover, Firebolt says it delivers analytics performance at an average 182 times faster speed than other data warehouses.
“While companies can store massive amounts of data, most organizations are only able to analyze a fraction of that big data, and they often find themselves looking at stale data that does not reflect the current state of their business,” Farkash told VentureBeat via email. “For companies to flourish today, they need to move fast, and they should not be forced to make data compromises to achieve only a small part of the business value that their data holds. With Firebolt, organizations can finally gain the insights they need without breaking the bank.”
Zeev Ventures led the series A funding round, with participation from TLV Partners, Bessemer Venture Partners, and Angular Ventures. It’s Firebolt’s first public round.
Gartner recently predicted that AI-derived business revenue will reach $3.9 trillion in 2022. With a pot that big, it’s no wonder investors are committing hundreds of millions of dollars. Analytics service provider Fractal Analytics raised $200 million in January 2019, months ahead of end-to-end data operations platform provider Unravel’s $35 million series C round. Not to be outdone, business analytics startup SiSense nabbed $80 million to expand its offerings last September. And Databricks raised $200 million at a $6.2 billion valuation last October.
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