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Dremio raises $160M for cloud data lake platform technology
The vendor is raising new money as demand for cloud data platform technology continues to grow as enterprises look to improve business intelligence and data analytics.
Dremio said on Jan. 25 it raised $160 million in a Series E round of funding, giving the data lake platform vendor a valuation of $2 billion.
The new funding came a year after Dremio raised $135 million in a Series D round as the vendor, based in Santa Clara, Calif., continues to build out its data lake platform.
The Dremio platform enables users to use cloud data storage for data lakes, with the ability to organize and query the data for business intelligence, operations and data analytics.
Dremio's funding success is being driven in part by overall market demand and interest in the data lake market. Rival data lake platform vendor Databricks was extremely active last year, raising a striking $1.6 billion in August 2021.
"We find that data lakes remain complex to deploy and manage based on our customer inquiries," said Forrester analyst Noel Yuhanna. "With most organizations dealing with data explosion, turning data into actionable insights is requiring considerable time and effort, as a result, impacting growth and innovation."
How Dremio's data lake platform helps organizations
Dremio is helping to accelerate business applications for data lakes in a number of ways, Yuhanna said. Dremio helps automate the ingestion, access and processing of data in data lakes for data scientists, business intelligence users, data engineers and other data consumers.
Noel YuhannaAnalyst, Forrester
In addition, Yuhanna noted that Dremio has data management expertise, especially as the creator of Apache Arrow, which enables in-memory analytics.
One of the key analytic trends in this decade will be unlocking the ability to analyze all of the data that traditionally has been too messy or arrived too quickly to analyze, said Hyoun Park, an analyst at Amalgam Insights.
"Dremio's funding reflects the massive market opportunity that exists in being able to analyze all of your data and the reality that market dominance in this new area of analytics will be decided in this decade," Park said. "Dremio's focus on accelerating queries and the compute side of analytics without having to invest in yet another database is an attractive starting point for companies seeking to move towards a data lake approach quickly."
Dremio data lake platform sailing toward IPO
As to why Dremio is raising money now, Tomer Shiran, co-founder and chief product officer, said the vendor has grown over the past year in terms of revenue and new customers, but still has not spent the money it raised in 2021.
In the meantime, the company realized there was a lot of investor interest in the technology and the market opportunity is large. He emphasized that in order to compete in the market, Dremio needs a "war chest" to finance ongoing technical and go-to-market efforts.
The general direction that Dremio is headed is toward an initial public offering (IPO), Shiran said.
"The goal here is to build a great standalone public company," he said. "We don't have a specific timeline in mind for an IPO, but it's definitely the path that we're headed."
Dremio data lake platform set to advance in 2022
Shiran has big plans for Dremio in 2022 as the vendor continues to build out its data lake platform.
In 2021, Dremio launched its Dart Initiative, a series of efforts designed to help accelerate data lake query performance. That effort to further improve performance with the Dart Initiative will continue in 2022, Shiran said.
Dremio's platform will also continue to expand its integration with the Apache Iceberg data lake table format open source project.
Iceberg, now at the foundation of Dremio's platform, competes with the Delta Lake open source technology created by Dremio's rival Databricks.
Dremio is also planning to integrate the Apache Arrow Flight SQL open source technology into its platform.
Apache Arrow Flight enables fast data movement to or from a data source, and Apache Arrow Flight SQL provides users with an integrated approach to rapidly access a database with SQL.
According to Shiran, the Flight SQL approach can make queries significantly faster than using Java database connectivity (JDBC) or open database connectivity (ODBC), which are typically used to enable queries.
Dremio is also looking to continue to develop and integrate the open source Project Nessie for data catalog capabilities in data lakes.
"There's a real opportunity to create a much better cloud-centric data metastore," Shiran said.