Data analytics startup Dremio has raised $135m in a D series, taking total funding to $250m, and achieving unicorn status ($1bn+ valuation). Competitor unicorn startup Starburst has pulled in $100m and Firebolt, another competitor, has taken in $37m.
The funding context is that cloud-based data warehouser Snowflake had a hugely successful IPO in September, 2020 and has a market cap of $80bn, at time of writing.
The shared dream here is to run fast data analytics on data from a variety of data sources. Dremio and Starburst say they do it simultaneously, without extracting the data you need and transforming it so it can be loaded into a single destination data warehouse. Instead you use software to combine different data sources into a single virtual data warehouse and analyse the data in that and in real time.
Firebolt says it performs extract, transform and load (ETL) much faster and more simply, and then runs faster analytics.
California-based Dremio’s software technology enables data analytics to access source data lakes, thus avoiding existing extract, transform and load (ETL) procedures to build a data warehouse. Its cloud data lake engine software runs in the AWS and Azure public clouds, or on-premises via Kubernetes or Docker, and uses executor nodes with NVMe SSDs to cache data.
Dremio has a Hub software entity that provides connectors for Snowflake, Salesforce, Vertica, AWS Redshift, Oracle, various SQL databases, and others to integrate existing databases and data warehouses.
Its performance claims seem almost outlandish; 3,000 times faster ad hoc queries, 1,700 times faster BI (Business Intelligence) queries and 90 per cent less compute needed than other SQL engines.
Total funding for Boston-based Starburst stands at $164m, including $100m raised recently at a $1.2bn valuation.
The technology is based on Facebook’s open source Presto distributed query project. It applies SQL queries across disparate data lakes and warehouses, such as Teradata, Oracle, Snowflake and others.
Starburst’s software runs in AWS, Azure, and Google Cloud or on-premises via Kubernetes.
Israel-based Firebolt, the newest of the three startups here, says it delivers the ultimate cloud data warehouse running analytics with extreme speed and elasticity. The company set up in 2019 and bagged $37m in A-round funding in December 2020.
The software has native support for semi-structured data and querying with SQL. Firebolt claims “semi-structured data can be analysed quickly and easily, without the need for complicated ETL processes that flatten and blow up data set size and costs.”
In other words, it runs ETL processes to get data into its more scalable data warehouse, and then queries the data faster.
Firebolt says its serverless architecture separates compute from its S3 data lake storage and provides an order-of-magnitude leap in performance. Customers can analyse much more data at higher granularity with lightning fast queries.
Download a Dremio Architecture Guide to find out more about its software. Download a Starburst Presto guide to read about its technology, and inspect a Firebolt document comparing its technology to Snowflake’s.