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.