Yellowbrick Data Looks To Shake Up The Data Warehouse Arena

Yellowbrick Data emerged from stealth this week, unveiling its all-flash analytics and data warehouse appliance that the startup says is magnitudes smaller and faster than current data warehouse systems.

The company also disclosed that it received $44 million in Series A funding from DFJ, Google Ventures, Samsung Ventures, Menlo Ventures and Third Point Ventures.

Many businesses today are struggling to gain value from the huge volumes and variety of data they are collecting, seeking ways to tap into that data for making both strategic and day-to-day operational decisions.

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"We are 100 percent-focused on providing a data warehouse to run business-critical workloads," said Neil Carson, Yellowbrick Data's CEO and co-founder, in an interview with CRN.

The data warehouse market includes system companies like Teradata, Oracle and IBM, as well as software vendors like Microsoft and SAP. Data warehouse projects have traditionally been costly and highly complex, leading to the rise of cloud-based data warehouse services such as Snowflake Computing and Amazon Web Services' Redshift.

Yellowbrick Data, founded in 2014, has developed a system architecture that's based on flash memory hardware and software developed to handle native flash memory queries. The appliance includes integrated CPU, storage and networking with data moving directly from flash memory to the CPU. The system's modular design can scale up to handle petabytes of data by adding analytic nodes.

The system includes an analytic database designed for flash memory, able to handle high-volume data ingestion and processing, and capable of running mixed workloads of ad hoc queries, large batch queries, reporting, ETL (extract, transform and load) processes and ODBC inserts.

The company says its system operates 140 times faster than conventional data warehouse systems for such tasks as retail and advertising analytics, security analysis and fraud detection, financial trading analysis, electronic health records processing and other applications.

The Yellowbrick Data Warehouse appliance occupies as little as 3 percent of the physical space of a legacy data warehouse, according to the company. It runs on premise, but also supports hybrid and private cloud environments, co-location and edge-computing networks.

"It has a massive price-performance advantage over anything out there," said Carson, who before founding the Palo Alto, Calif.-based company, was CTO at flash storage system pioneer Fusion-io.

Cloud data warehouse systems like Snowflake and AWS Redshift have been getting a lot of attention lately. But Carson argued that if a data warehouse system is running 24 hours a day, "the economics of public cloud just doesn't work."

So while he says Yellowbrick Data will likely have a public cloud offering in the future, the company's focus for now is co-location, private cloud and hybrid cloud environments. "The world will be hybrid at the end of the day," he said.

Yellowbrick Data has actually been selling its system to select customers, including Overstock.com and TEOCO Corp., for nearly a year.

The company is now in the process of developing a partner program and Carson described the Yellowbrick Data Warehouse as "a very channel friendly product."

The company will be recruiting solution provider partners with deep data warehousing expertise. Carson specifically mentioned solution providers who work with data warehouse appliances from IBM, originally developed by Netezza, which IBM acquired in 2010.

Yellowbrick Data is eyeing the same kind of go-to-market channel strategy as used by vendors like hyper-converged system maker Nutanix and secondary storage system vendor Cohesity, said chief marketing officer Gary Orenstein, in the interview with CRN.

Much of the venture funding is being used for developing go-to-market plans, including the channel, and expanding the company's sales operations, the CMO said.

The company is targeting "greenfield" opportunities among larger businesses that need data warehouse systems for new applications or are looking to replace legacy data warehouse systems, Carson said.