The case for a warehouse-native CDP starts with control and data centralization. In this model, the data warehouse becomes the single source of truth, with tools layered on top for identity resolution, segmentation and activation.
"These actions reflect targeted adjustments to align our teams with Snowflake's long-term strategy. Such steps are a natural part of scaling a fast-growing company, and we remain firmly committed to sustained growth."
Snowflake Inc. ( NYSE:SNOW) provides the data cloud infrastructure that AI applications depend on, but its path to profitability remains uncertain. The company reported Q3 2026 revenue of $1.21 billion, beating estimates of $1.18 billion with 29% year-over-year growth. Product revenue reached $1.16 billion, while the company maintained a strong 125% net revenue retention rate. CEO Sridhar Ramaswamy highlighted that Snowflake Intelligence, the company's AI capabilities platform, achieved the fastest adoption rate of any product launch in company history.
Snowflake offers a fully managed data platform, but Sumo Logic users often lack insight into performance, login activity, and operational health. The Sumo Logic Snowflake Logs App analyzes login and access activity to identify anomalies or suspicious behavior. It also optimizes data pipelines with insights into long-running or failing queries. Teams can centralize log data to facilitate correlation across applications, cloud services, and data platforms.
Snowflake ( ) released its third-quarter earnings yesterday, posting results that topped Wall Street estimates. Product revenue climbed 28% year-over-year to $1.21 billion, while adjusted earnings hit $0.35 per share, beating the consensus estimate of $0.31. Yet, the stock plunged 11% in midday trading today as investors fixated on the company's fourth-quarter guidance .
Databricks and Snowflake are at it again, and the battleground is now SQL-based document parsing. In an intensifying race to dominate enterprise AI workloads with agent-driven automation, Databricks has added SQL-based AI parsing capabilities to its Agent Bricks framework, just days after Snowflake introduced a similar ability inside its Intelligence platform. The new abilities from Snowflake and Databricks are designed to help enterprises analyze unstructured data, preferably using agent-automated SQL, backed by their individual existing technologies, such as Cortex AISQL and Databricks' AI Functions.
SnowConvert AI excels at static code conversion, but it still requires code extraction and re‑insertion. Hyper‑Q complements this with on‑the‑fly translation to tackle dynamic constructs and application‑embedded SQL that converters often miss,
Data-storage company Snowflake filed an 8-K with the SEC on Monday after an executive spoke to an influencer who posts under the account name "theschoolofhardknockz" on Instagram and TikTok. Though the filing doesn't name the executive, he identifies himself as Chief Revenue Officer Mike Gannon in the video, which had more than 555,000 views on TikTok and nearly 138,000 likes on Instagram as of Wednesday afternoon.
Customers have been using Spark for a long time to process data and get it ready for use in analytics or in AI. The burden of running in separate systems with different compute engines creates complexity in governance and infrastructure.
The addition of the managed PostgreSQL database to the Data Intelligence platform will allow developers to quickly build and deploy AI agents without having to concurrently scale compute and storage.
Lakeflow and OpenFlow reflect two philosophies: Databricks integrates data engineering into a Spark-native, open orchestration fabric, while Snowflake's OpenFlow offers declarative workflow control.
