
"Google recently introduced a columnar engine for its globally distributed database, Spanner, intending to resolve the long-standing conflict between online transaction processing (OLTP) and analytical query processing (OLAP). The new feature, currently in preview, allows Spanner (Enterprise and Enterprise Plus editions) to handle both workloads simultaneously on a single database, eliminating the need for separate data warehouses and complex ETL (Extract, Transform, Load) pipelines."
"Historically, organizations have used row-oriented databases for high-volume, low-latency OLTP workloads, while offloading analytics to separate data warehouses with columnar storage. With the columnar engine, the need for separation is not necessary as it features a hybrid architecture that transparently maintains a secondary copy of the data in a columnar format, optimized for analytical queries. When a query is executed, Spanner's optimizer intelligently directs it to either the existing row-based storage for fast transactional lookups or the new columnar storage for large-scale scans and aggregations."
Google introduced a columnar engine for Spanner to bridge OLTP and OLAP workloads on one platform. The feature is in preview for Spanner Enterprise and Enterprise Plus editions. The engine maintains a secondary columnar copy of data alongside row-oriented storage, letting the optimizer route transactional lookups to row storage and large-scale scans and aggregations to columnar storage. The architecture uses vectorized query execution that processes data in batches to boost performance. The columnar engine can accelerate analytical queries up to 200X on live operational data. The capability reduces the need for separate data warehouses and complex ETL pipelines and supports real-time AI workloads.
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