Presto, an open source distributed SQL engine, is widely recognized for its low-latency queries, high concurrency, and native ability to query multiple data sources. Proven at scale in a variety of use cases at Comcast, GrubHub, FINRA, LinkedIn, Lyft, Netflix, Slack, Zalando, in the last few years Presto experienced an unprecedented growth in popularity in both on-premises and cloud deployments over Object Stores, HDFS, NoSQL and RDBMS data stores.
Delta Lake, a storage layer originally invented by Databricks and recently open sourced, brings ACID capabilities to big datasets held in Object Storage. While initially designed for Spark, Delta Lake now supports multiple query compute engines including Presto.
In this talk we discuss how Presto enables query-time correlations between Delta Lake, Snowflake, and Elasticsearch to drive interactive BI analytics across disparate datasets.
Presto, an open source distributed SQL engine, is widely recognized for its low-latency queries, high concurrency, and native ability to query multiple data sources. Proven at scale in a variety of use cases at Comcast, GrubHub, FINRA, LinkedIn, Lyft, Netflix, Slack, Zalando, in the last few years Presto experienced an unprecedented growth in popularity in both on-premises and cloud deployments over Object Stores, HDFS, NoSQL and RDBMS data stores.
Delta Lake, a storage layer originally invented by Databricks and recently open sourced, brings ACID capabilities to big datasets held in Object Storage. While initially designed for Spark, Delta Lake now supports multiple query compute engines including Presto.
In this talk we discuss how Presto enables query-time correlations between Delta Lake, Snowflake, and Elasticsearch to drive interactive BI analytics across disparate datasets.
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