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data analytics

MotherDuck secures investment from Andreessen Horowitz to commercialize DuckDB • ZebethMedia

Jordan Tigani — a founding engineer at Google BigQuery, Google’s fully managed data analysis platform — was working as the chief product officer at SingleStore when he noticed that the vast majority of database workloads were small (less than 10GB in size) and low-bandwidth. While vendors were building for massive data sets, the term “big data” was becoming a misnomer thanks to recent advances in hardware, the way Tigani saw it. Around the same time, Tigani got in touch with Hannes Mühleisen, the co-creator of the lightweight database platform DuckDB, to toss ideas for a paid service back and forth. Seeking to launch a product for developers with light database requirements, Tigani — with Mühleisen’s blessing — began building a DuckDB-based cloud service. The service became the cheekily named MotherDuck, a startup independent of the original DuckDB that’s focused on commercializing open source DuckDB packages. “Users want easy and fast answers to their questions — they don’t want to wait for the cloud,” Tigani told ZebethMedia via email. “The fact is that a modern laptop is faster than a modern data warehouse. Cloud data vendors are focused on the performance of 100TB queries, which is not only irrelevant for the vast majority of users, but also distracts from vendors’ ability to deliver a great user experience.” It’s a classic playbook — take an open source tool and build a service on top of it. But while it might not be original, Tigani’s plan has already paid dividends. MotherDuck today announced that it raised $47.5 million across seed and Series A rounds, valuing the company at $175 million post-money. Redpoint led the seed while Andreessen Horowitz (a16z) led the Series A — other investors include Madrona, Amplify Partners and Altimeter. Tigani says that MotherDuck wasn’t planning to raise the Series A so soon after the seed, but did so at the urging of LPs — and for the opportunity to work with a16z. “With this funding, MotherDuck is able to build out their world-class engineering team and add a go-to-market function to provide a cloud analytics platform for organizations that want to use DuckDB in an evolved way,” Tigani said. “At the same time, it allows DuckDB to continue to be a vehicle for academic research.” Tigani claims that MotherDuck’s service — powered by DuckDB, which HackerNoon once described as “mutant offspring of SQLite and Redshift” — allows practitioners to start answering questions from data faster than most existing tooling. It uses local computing resources in concert with the cloud, driving data analytics and other data-heavy workloads.  That’s in contrast to typical data warehouse systems that offer reporting and tools almost exclusively for enterprise-scale analytics. As Madrona’s Jon Turow explains in a forthcoming blog post (ZebethMedia got a sneak peak), MotherDuck uses a “hybrid execution” technique to query a data set that’s spread across multiple places. Some of the data might be on a developers laptop, some in the cloud instance and the rest in a different cloud, but MotherDuck makes it possible for a dev to query the combination of these sources. “The platform intelligently decides where to operate upon each bit of data to minimize the costs of compute and data transfer,” Turow writes. The data warehouse concept has existed since the ’80s, but it’s risen to prominence in recent years as companies shift their workloads to the cloud. There’s startups like Firebolt and Hydra, which aim to become the open cloud data warehouse of choice for large companies. Panoply, another player in the data warehouse space, has taken a different approach, developing tools that make it easier for businesses to analyze their data with standard database queries. While Tigani sees MotherDuck as a competitor in the data analytics market alongside data warehouse vendors, he positions the platform as the technological superior alternative.  “The high efficiency of DuckDB will allow MotherDuck to be cost-competitive, while also being more performant for most data workloads,” Tigani asserted. “Advances in CPU, memory, disk performance and networks are making existing architectures obsolete. Large distributed analytics clusters are no longer necessary due to these advances. Single-node DuckDB can often be much faster, cheaper and simpler than these distributed systems.” The DuckDB team is involved to a degree with MotherDuck, which in turn is a member of the DuckDB Foundation, the nonprofit that holds much of DuckDB’s IP. DuckDB’s own commercial arm, DuckDB Labs, is a shareholder in the company and contributed code to the cloud platform. Tigani assures me that DuckDB will continue to be freely available under a permissive MIT license and that the original DuckDB team will build, maintain and promote the core DuckDB codebase going forward. Fueled by the fresh capital, MotherDuck plans to expand its small workforce from 13 people to 18 by the end of the year. When asked, he declined to answer questions about the size of the startup’s customer base or revenue, saying it’s too early.

Analytics operating system Redbird makes data more accessible to non-technical users • ZebethMedia

Data engineers have a big problem. Almost every team in their business needs access to analytics and other information that can be gleaned from their data warehouses, but only a few have technical backgrounds. Redbird was created to help everyone in an organization create and run analytics without using code, therefore reducing the amount of bottlenecks that data engineers need to deal with. The New York-based startup announced today that it has raised $7.6 million in an oversubscribed seed round led by B Capital, with participation from Y Combinator, Thomson Reuters Ventures, Alumni Ventures and Soma Capital, along with other funds and angel investors. Redbird, formerly known as Cube Analytics, serves as an analytics operating system by connecting all of an organization’s data sources into a no-code environment that non-technical users can use to perform analysis, reporting and other data science tasks. The new funding will be used to add more no-code capabilities. It also plans to build out its marketplace, where users and developers can exchange apps they create using Redbird. Founded by data analytics experts Erin Tavgac and Deren Tavgac, Redbird works with large enterprises in a wide array of verticals including consumer packaged goods, manufacturing, retail, media and agencies. Erin formerly worked at McKinsey, helping companies set up and run data analytics capabilities, while Deren was chief product officer at Saks Fifth Avenue. Erin told ZebethMedia that the two left their jobs to solve enterprise data analytics problems like lack of automation and advanced analytics that require coding skills. That means data engineering teams can’t meet all demand from stakeholders, leaving companies unable to manage the fragmented tools within a complex data stack. Redbird addresses these issues by enabling people without a technical background to create custom apps that automate analytics, breaking through bottlenecks for data engineering teams while giving everyone access to data analytics. Redbird’s peers in the enterprise data analytics space include basis analytic tools like Tableau, Looker and Microsoft Power BI, which Tavgac said Redbird does not consider direct competitors because they don’t automate complex workflows end-to-end, instead delivering generic data visualizations from datasets that have already been transformed. A closer rival are advanced automation platforms like Alteryx, but it has a couple drawbacks compared to Redbird. For one thing, it has less capabilities in collection, data science and visualization, which means customers can’t use it as a comprehensive analytics workflow solution, Tavgac said. It is also hard for non-technical users to adopt, a problem that Redbird was created to solve. Most of Redbird’s customers are large enterprises that make more than $1 billion in revenue. It is profitable, with seven-figure revenue and 9x revenue growth over the past year. Redbird monetizes through an enterprise SaaS model, with usage-based license fees. Some examples of how clients have used Redbird: a large media company created automation workflows that collect data from more than 10 sources, apply advanced analytics to them and generate thousands of custom reports to guide their ad sale activities. A global CPG brand is using Redbird to do digital brand health tracking across a wide variety of data sources, like social media, e-commerce review and Google search volume, and using advanced analytics to predict future sales trend. In a statement, B Capital general partners Karen Page said, “We believe Redbird will become a mission-critical platform for enterprises to manage complex data workflows. This investment underscores our strategy of working with innovative companies that enable rapid technological transformation across traditional industries.”

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