When Apple launched its App Store in 2008, it opened a window of opportunity for thousands of software developers who rushed to invent the mobile-first world in which we all live today. Vendors that embraced the new paradigm, such as game developer Imangi, saw breakthrough success. Products such as Temple Run capitalized on the iOS platform to the tune of over one billion downloads.1 At Snowflake Ventures, we see a similar window opening for B2B SaaS vendors across all lines of business that can plug into the underlying data infrastructure of their customers. 

While the introduction of SaaS applications has democratized software and driven huge productivity gains, an unintended consequence is that companies have ended up with multiple data silos across their different lines of business. API integrations are tough to build and maintain at scale, and departments or entire enterprises that rely on these SaaS solutions continue to struggle with consolidating data sets. Think about marketing and product teams trying to build a Customer Data Platform by combining data from CRMs and marketing suites with ad campaign performance and behavioral event data, IT teams combining asset inventory with endpoint telemetry, or security teams tracking key risk indicators across their various tools. 

As Tomasz Tunguz put it in his Cloud Prem Architecture article,2 we’re starting to see great momentum in a new model where SaaS applications are split into code and data. The SaaS company writes, updates, and maintains the code, and the customer provides its cloud data infrastructure for SaaS vendors to use for storing data and for the application’s data processing. This avoids the need to manage API integrations, opens new opportunities for multi-dimensional insights and, importantly, means that new SaaS solutions can be added without creating new data silos.

A great example of this is in the security analytics space. Historically, security teams have collected their data in dedicated Security Information and Event Management (SIEM) solutions. These systems operate separately from the rest of the enterprise’s data stack, with painful limits on scale and flexibility. As a result, most security organizations must contend with multiple data silos without support from the rest of the business.

To remove these limitations and meet the security needs of their fast growing businesses, innovative leaders such NETGEAR’s Pallavi Damle are embracing the Data Cloud. As Head of Global Cybersecurity, Damle achieved her visibility and automation goals, along with significant cost savings, by moving from a dedicated SIEM solution to running security analytics alongside NETGEAR’s other analytics workloads on Snowflake. This successful shift was enabled by the SaaS solution that NETGEAR purchased from Hunters.3 Hunters, a Powered by Snowflake partner and Snowflake Ventures portfolio company, provides cyberthreat detection and response capabilities that customers can run standalone or on top of their existing Snowflake platform.

Like an app on an iPhone, Hunters loads security data into NETGEAR’s Snowflake account and powers its interface and automation with NETGEAR’s Snowflake compute resources. Its direct access to NETGEAR’s Snowflake resources means that Hunter’s threat detection engine combines more-complete and diverse data sets, and if there’s a security incident that requires a big investigation, the NETGEAR information security team can quickly scale query power as needed. NETGEAR is in control. It’s an attractive model, and it played a key role in NETGEAR becoming a Hunters customer. Gartner MQ leaders such as Securonix4 (see the press release5) and exciting new players such as Panther Labs6 are also adopting this innovative approach.

For vendors leveraging this model, there are several advantages:

  • Go-to-market alignment: Snowflake has a consumption-based sales model and Snowflake sales reps are always looking for new use cases and workloads that can provide customer value and drive consumption within Snowflake’s 4,500+ customers as of April 30, 2021. 
  • Data compliance: This model directly addresses the need customers often have to keep data in their infrastructure and control in order to meet security and compliance requirements. This is especially relevant in highly regulated industries. 
  • Data science workloads: Vendors are able to add value to larger enterprises whose data science teams can extract additional value from having direct access to raw data, especially in combination with other business data sets. 
  • Gross margin improvement: There can be a reduction in cost of goods sold (COGS) for vendors because the end customer provides the storage and compute resources used by the application.

For customers, the value is clear. They are able to stop creating data silos and maintain control of their data, while empowering additional departments and lines of business to gain value from an enterprisewide data-driven strategy. 

We continue to see great momentum in this new breed of forward-thinking SaaS businesses. Institutional venture capitalists have taken note and are increasingly interested in aligning their investing strategies with this new wave of innovation empowered by the Data Cloud. The window of opportunity is now!

To learn more about how to become a Snowflake partner, please contact Matt Hill from the Powered by Snowflake team at [email protected]. This new Powered by Snowflake program guides vendors on how to design and implement applications that can run directly on a customer’s Snowflake platform. The program also helps partners after launching their joint solution to raise awareness among Data Cloud users.

If you’re already a partner and would like to connect with Snowflake Ventures, please contact us at [email protected].

  1.  bit.ly/2TG4IsB
  2. bit.ly/3kLWI4x
  3. hunters.ai
  4. securonix.com
  5. bit.ly/3zxvzpU
  6. runpanther.io