Dremio raises $160 million for cloud data lake platform technology
Dremio today said it raised $160 million in a Series E funding round, giving the data lake platform provider a $2 billion valuation.
The new funding comes a year after Dremio raised $135 million in a D-Series lathe as the Santa Clara, Calif.-based supplier continues to develop its data lake Platform.
The Dremio platform enables users to use cloud data storage for data lakes, with the ability to organize and query data for business intelligence, operations and data analysis .
Dremio’s funding success is in part due to overall market demand and interest in the data lake market. Rival data lake platform provider Databricks was extremely active last year, raising an impressive $1.6 billion in August 2021.
“We find that the data lake remains complex to deploy and manage based on the demands of our customers,” said the Forrester analyst. Christmas Yuhanna. “With most organizations facing the data explosion, turning data into actionable insights takes significant time and effort, impacting growth and innovation.”
How Dremio’s Data Lake Platform Helps Organizations
Dremio helps accelerate business applications for data lakes in several ways, Yuhanna said. Dremio helps automate data ingestion, access, and processing in data lakes for data scientists, business intelligence users, data engineers, and other data consumers.
Additionally, Yuhanna noted that Dremio has expertise in data management, especially as a creator of apache arrowwhich allows in-memory analysis.
One of the major analytics trends of this decade will be to unlock the ability to analyze all data that has traditionally been too messy or arrives too quickly to analyze, said Hyun Parkanalyst at Amalgam Insights
“Dremio’s funding reflects the huge market opportunity that exists to be 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 computational side of analysis without having to invest in another database is an attractive starting point for companies looking to quickly transition to a lake approach. of data.”
Dremio data lake platform sails towards IPO
As to why Dremio is fundraising 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 no spent the money he raised in 2021.
In the meantime, he realized that there is a lot of investor interest in the technology and the market opportunity is great. He pointed out that to be competitive in the market, Dremio needed a “war chest” to fund ongoing technical and go-to-market efforts.
The general direction Dremio is heading is toward an initial public offering (IPO), Shiran said.
“The goal here is to build a large self-sustaining public company,” he said. “We don’t have a specific timeline in mind for an IPO, but that’s definitely the path we’re headed in.”
Dremio data lake platform expected to progress in 2022
Shiran has big plans for Dremio in 2022 as the vendor continues to develop its data lake platform.
In 2021, Dremio launched its darts initiative, a series of efforts designed to speed up the performance of data lake queries. This effort to further improve performance with the Dart initiative will continue into 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, today the basis of the Dremio platform, competes with the Delta Lake open source technology created by Dremio rival Databricks.
Dremio also plans to integrate Apache Arrow Flight SQL open source technology into its platform.
Apache Arrow Flight enables rapid movement of data to or from a data source and Apache Arrow Flight SQL provides users with an integrated approach to quickly access a database with SQL.
According to Shiran, the Flight SQL approach can make queries much faster than using JDBCName (Java database connectivity) or ODBC (open database connectivity), which are typically used to enable queries.
Dremio also seeks to continue to develop and integrate open source Project Nessie for data catalog capabilities in data lakes.
“There is a real opportunity to create a much better cloud-centric data metastore,” Shiran said.