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Lazy Beats Smart and Fast

Julian Hyde Julian Hyde | Senior Staff Engineer | Google

Did you know that databases often “cheat”? Even with a scalable query engine and smart optimizer, many real-world queries would be too slow if the engine read all the data, so the engine re-writes your query to use a pre-materialized result. B-tree indexes made the first relational databases possible, and there are now many flavors of materialization, from explicit materialized views to OLAP-style caching and spatial indexes. Materialization is more relevant than ever in today’s heterogenous, distributed systems.

If you are evaluating data engines, we describe what materialization features to look for in your next engine. If you are implementing an engine, we describe the features provided by Apache Calcite to design, maintain and use materializations.

Julian Hyde
Julian Hyde
Senior Staff Engineer | Google

Julian Hyde is the original developer of Apache Calcite, an open source framework for building data management systems, and Morel, a functional query language. Previously he created Mondrian, an analytics engine, and SQLstream, an engine for continuous queries. He is a staff engineer at Google, where he works on Looker and BigQuery.

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