Upsolver Eyes Ease Use of Cloud Data Lakes
April 9, 2021
secured $25 million in Series B financing led by Scale Venture Partners
(Scale). Existing investors JVP, Vertex Ventures US, and Wing Venture
Capital also participated in the round. As part of the investment, Ariel
Tseitlin — Partner at Scale and former Head of Netflix Cloud Solutions —
has joined Upsolver’s board of directors. The company also announced its
free Upsolver Community Edition, an integral part of the Upsolver
platform that delivers on its vision for universal access to cloud data.
The new funding comes on the heels of Upsolver’s $13 million Series A
and follows a tripling of the company’s revenue in 2020, including the
addition of marquee customers such as Cox Automotive, Wix, and AppsFlyer.
Upsolver will use the financing to aggressively build its team, scale
its go-to-market engine, and drive technical innovation.
Companies are rapidly migrating their organizational data into
cost-effective cloud data lakes. However, making the data valuable for
analytics requires complex engineering projects that take months to
complete and rely on unicorn data engineers skilled in distributed
systems like Apache Hadoop or Apache Spark.
With Upsolver, cloud analytics can be both cost-effective and agile.
Upsolver addresses the complex challenge of transforming raw, big data
into structured tables with a visual SQL IDE that any data practitioner
can use, combined with an execution engine that automates data lake
engineering to ensure high-performance. Since Upsolver is based on open
source file formats like Apache Parquet, companies avoid vendor lock-in
and can take advantage of a multitude of query engines such as PrestoDB,
Trino, and Athena, or data systems like Snowflake, AWS Redshift, Azure
Synapse Analytics, Splunk, and Elasticsearch.
analytics platforms are a thing of the past. Today’s organizations
require a variety of analytics tools to fully capitalize on their data,”
said Ariel Tseitlin, Partner at Scale. “Data lakes originally promised
this variety and openness but also required a large, ongoing investment
in engineering. Upsolver eliminates this trade-off. The company’s steep
growth curve, top-quartile net revenue retention, and superior
technology prove its leadership in the cloud data space. We’re thrilled
to back the team.”
Ori Rafael (Rafael) and Yoni Eini (Eini), two database engineers,
founded Upsolver after experiencing firsthand the frustration and
complexity of building a cloud analytics solution using Spark. “We
wanted to store data affordably in the cloud without analytics vendor
lock-in,” said Rafael. “Unfortunately, what used to take three hours
using SQL turned into a month or more of hand-coding and hundreds of
configurations in Spark. We created Upsolver to transform cloud
analytics into an agile process."