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AI & Enterprise

Databricks unveils unified architecture for operational and analytics data, targeting AI agents

Databricks on Monday unveiled a new data architecture that integrates transactional databases and analytics systems. At its Data+AI Summit in San Francisco, the company introduced its lake transactional/analytical processing (LTAP) architecture and a real-time analytics engine designed to deliver millisecond responses without separate systems. Databricks said LTAP uses a single dataset in a data lake for both operational and analytics workloads, removing the need for CDC pipelines, ETL processing and replica databases.

AI & Enterprise

Observability competition heats up as Snowflake pushes data platform edge

Snowflake entered the observability market after acquiring Observe in January, putting it in competition with Cisco-owned Splunk, Datadog and New Relic. Jeremy Burton (제레미 버튼), Observe founder and head of Snowflake\'s observability business, said Snowflake’s data platform can strengthen competitiveness by addressing fragmented data and high costs. He also highlighted AI agents, and Snowflake’s launch of PG Lake and a public preview of Data Mirroring at Snowflake Summit 26 in San Francisco.

AI & Enterprise

Snowflake boosts enterprise data and AI interoperability features

Snowflake on Monday unveiled interoperability features that let companies use Snowflake data as well as external data lakes and open-system data under a single governance model without moving or duplicating data. The announcement was made at the Snowflake Summit 26 annual conference in San Francisco. The company highlighted the general release of Apache Iceberg v3 and Snowflake support for Iceberg tables, plus Horizon Catalog based on Apache Polaris and new integrations with major platforms.