Data by itself isn’t very useful. Data only becomes useful as it’s understood and as it infuses application experiences. This desire to put data to work has driven a boom in cloud-based analytics. Though a relatively small amount of IT spending currently goes to cloud—roughly 6% according to IDC in 2020—all of the momentum is away from on-premises, legacy business intelligence tools toward more modern, cloud-native options like Google BigQuery, Amazon Redshift, Databricks, or Snowflake. The popularity of bringing data and cloud together shows up in Snowflake’s rocketing rise up the DB-Engines database popularity rankings, from number 170 back in November 2016 to number 11 in January 2023. Some of Snowflake’s success absolutely comes down to performance, scalability, the separation of storage and compute, and other benefits.
But arguably an even bigger benefit is simply cloud. Snowflake was born in the cloud and offers a natural path for enterprises looking to move to the cloud. Yes, that same cloud keeps propelling new databases forward against legacy alternatives. That same cloud promises to continue to upend the world of data in 2023.
While I don’t agree fully with my InfoWorld colleague David Linthicum that “2023 could be the year of public cloud repatriation,” I can agree that we shouldn’t blindly fall in love with a technology or see it as a hammer and hence treat every business problem as a nail. Cloud solves many problems, but not all. In areas related to advanced data-driven applications, however, cloud is indispensable, as Linthicum acknowledges: “When advanced IT services are involved (AI, deep analytics, massive scaling, quantum computing, etc.), public clouds typically are more economical.”
Not only more economical, but also more practical.
Years ago AWS executive Matt Wood made this case to me, and it’s as persuasive today as it was in 2015. “Those that go out and buy expensive infrastructure find that the problem scope and domain shift really quickly,” he said. “By the time they get around to answering the original question, the business has moved on.” As he continued, “If you drop a huge chunk of change on a data center that is frozen in time,” the questions you can ask of your data are stuck in a time warp. Even in straitened economic times, the exact wrong way to think of cloud is through a narrow lens of cost. Elastic infrastructure begets flexibility in making sense of data. Dollars from sense, as it were, rather than dollars and cents. That’s cloud-based analytics tools.
Companies seem to understand this. At a recent analyst conference, Snowflake CFO Mike Scarpelli talked about competitive dynamics in the data warehousing market. “We are never competing with Teradata [an incumbent data analytics company founded in the on-premises software era]. When a customer has made the decision to go off-prem, it is never against Teradata.
