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Snowflake’s AI Data Cloud lets organizations bring their data together, analyze it, build applications and use AI. Customers can also share data with other organizations through the platform rather than copy and move it. These activities use the same integrated service, though customers can choose which capabilities they need.
Nearly all revenue comes from platform usage, with existing customers supplying most of it. Customers either commit to buying capacity, typically paying annually in advance, or pay monthly for on-demand use. What they spend depends on how much computing, storage and data transfer they consume, so signed contracts alone do not determine the pace of revenue.
Snowflake runs on AWS, Microsoft Azure and Google Cloud, with most of its business on AWS. These infrastructure suppliers also compete with it, and their pricing materially affects Snowflake’s costs. Data-localization and cross-border transfer rules constrain where data can be stored and moved. In China, law requires Snowflake to serve certain multinational customers’ Chinese affiliates through a Chinese-owned operating partner that controls parts of the platform and acts as the seller.
The risk section is the longest, dullest part of the filing. This keeps only what can really hurt you: where it hits, how hard, when it plays out.
Every company claims an edge. Each one is checked against hard numbers like margins and returns: which hold, and which line gives way first.
TERADATA CORPORATION competes directly with Snowflake for large organizations paying to store and analyze data, through its enterprise data warehouse and analytics platform.
MongoDB competes more directly with Snowflake as Snowflake expands into databases that run applications: both sell managed cloud data platforms to enterprises. Watch adoption of MongoDB Atlas, which runs and manages customers’ databases in the cloud, for a read on demand in this overlapping market.
Microsoft both competes for Snowflake’s cloud data customers through Azure and sells Snowflake infrastructure to run its platform. Azure infrastructure pricing matters to Snowflake’s costs and gross margins.
Amazon’s AWS competes for Snowflake’s cloud data customers while also charging Snowflake for the infrastructure its platform uses. Watch AWS infrastructure pricing: it affects how much gross profit Snowflake keeps from customer usage revenue.
Alphabet’s Google Cloud competes with Snowflake for cloud data services while supplying the GCP infrastructure on which Snowflake runs. Changes in that infrastructure’s pricing affect Snowflake’s costs and gross margins.
Oracle competes with Snowflake for enterprises paying to manage their data, selling database and cloud analytics products that address those workloads.
Elastic N.V. and Snowflake both sell enterprises data platforms for analytics and AI, competing for parts of their search and data-processing work. Watch customers’ expanding use of Elastic Cloud, whose paid subscriptions are priced by resources, as a signal of demand for these platforms.
Datadog and Snowflake both have exposure to enterprises expanding or optimizing cloud workloads: customers pay Datadog to monitor applications and infrastructure, and Snowflake to process and store data. Datadog’s infrastructure and application monitoring business is the part to watch for that shared demand.
Dynatrace, Inc. and Snowflake share exposure to enterprises’ growing cloud workloads and data volumes: Dynatrace sells a platform that consolidates monitoring and business data in Grail, while Snowflake charges for processing data for analytics and AI. Watch enterprise use of Grail for a view of demand to bring that data together.
Amazon.Com Inc earningsAMZN
Amazon’s AWS charges Snowflake for cloud infrastructure and competes for enterprise cloud-data business, so its report can shed light on Snowflake’s serving costs and competitive pressure.
First look for any disclosed changes in infrastructure prices; those bear more directly on Snowflake’s cost of running its platform than AWS’s overall cloud margin does. Higher prices would raise Snowflake’s cost to serve each unit of cloud usage and could pressure product margin; stable or lower prices would mean less cost pressure. Then read AWS cloud growth as a signal of demand for cloud workloads and of AWS’s own position in that market—not as proof that Snowflake’s usage or costs changed by the same amount. Together, these clues help distinguish supplier-cost pressure from a competitor’s growth.
Datadog, Inc. earningsDDOG
Datadog earns revenue by monitoring companies’ cloud applications and infrastructure, giving Snowflake a read-through on demand for the cloud workloads that also generate data-processing needs.
Watch growth in Datadog’s monitoring business. If companies are expanding their use of monitoring, they are still running or managing more cloud applications and infrastructure—a demand backdrop consistent with more need to process and store data at Snowflake. If that business slows, companies may be reining in cloud workloads, a weaker backdrop for Snowflake too. Datadog sells monitoring, not Snowflake’s platform, so its report is a demand signal, not a substitute for Snowflake’s own usage figures.
TERADATA CORPORATION earningsTDC
Teradata competes directly with Snowflake for large organizations’ data-warehouse and analytics spending, so its report shows whether that shared market is active and how strong the rivalry may be.
Watch Teradata’s data-warehouse and analytics business. Stronger demand or sales would show that large organizations are still paying to store and analyze data, while also showing that a direct rival is competing for that spending. Weaker business could mean the shared market is softening; it would not by itself mean Snowflake is winning customers. The takeaway is whether this market has demand behind it and how much competition Snowflake faces—not how Snowflake itself performed.
Snowflake Inc. earningsThis company
Snowflake recognizes most platform revenue as customers use its services, so this report will show whether rising customer usage is growing product revenue without eroding product margins.
Read product-revenue growth alongside product gross margin. Revenue reflects customers’ consumption of compute, storage and data transfer; margin shows how much is left after product costs. Faster growth with a steady or rising margin means customers are using more without Snowflake giving up more of each revenue dollar. Slower growth or a falling margin points to weaker consumption or rising costs, such as cloud infrastructure, absorbing more of the revenue. Together, the figures show whether usage growth is holding up and paying its way.
