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BigQuery is pretty fast anyway so you d really need to value the extra speed
Lindsay Clark Mon 1 Mar 2021 // 18:33 UTC Share
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Google has introduced a caching layer in Big Query - its cloud data warehouse - designed to speed up responses to users as they explore and experiment with data.
Under the moniker BI Engine, the data layer is designed to bridge the gap between BI tools that are built for interactivity like Tableau, which extracts data from the data warehouse, and an in-memory database for greater interactivity and Google s Looker, which queries data directly.
“The cloud databases. like BigQuery weren t built to support interactive BI, they were built for scale event analytics and scale-type questions,” said Colin Zima, chief analytics officer with Looker, the cloud BI biz Google bought for $2.6bn in February 2020.
Snowflake? We can query that
Lindsay Clark Thu 17 Dec 2020 // 16:15 UTC Share
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Updated Enterprise data warehouse stalwart Teradata has capped a difficult year with an update to Teradata QueryGrid, which promises to connect customers to a vast array of new data sources – a decidedly underwhelming move, according to some.
Teradata has partnered with Starburst Data to integrate a new Presto connector so that users of Teradata s Vantage analytics platform can access and query a gamut of cloud and on-premises data sources.
Document store database MongoDB, Databricks Delta Lake, columnar database Apache Cassandra, as well as cloud data warehouses Amazon Redshift and Google BigQuery were listed by Teradata as the data sources at users fingertips as a result. In its publicity material Teradata somehow forgot to mention that the tool also connects them to Snowflake, the headline-grabbing cloud data warehouse stock-market smash of the year.