![]() You can use a COPY command with COMPUPDATE PRESET to enable Amazon Redshift to choose the compression encoding. You can use a Lake Formation Data Catalog with Amazon Redshift Spectrum. You can set the query priority of an automatic WLM queue. You can encode some columns with AZ64 compression encoding. You can create tables with default IDENTITY columns. You can use the BOOST option when vacuuming tables. Updated the guide to describe the new Amazon Redshift console.Īmazon Redshift can automatically sort table data. Updated the guide to describe support for spatial data. Updated the guide to describe new parameters of the UNLOAD command. Updated the guide to describe federated query with an updated CREATE EXTERNAL SCHEMA. You can use an ALTER TABLE command with the ALTER DISTSTYLE ALL clause to change the distribution style of a table. Materialized views are generally available starting with cluster version 9.Ĭolumn-level privileges are available starting with cluster version 9. Support for materialized views general availability Updated information about querying data with federated queries.Īdded descriptions of additional spatial functions. Support for federated query general availability Updates to commands and views that manage storage controls for schemas. You can write to external tables by running CREATE EXTERNAL TABLE AS SELECT to write to a new external table or INSERT INTO to insert data into an existing external table. You can create materialized views in Amazon Redshift that reference external data sources. Materialized view support external tables Support for enhancements to querying spatial dataĮnhancements include loading a shapefile and several new spatial SQL functions. You can now alter a table column encoding.Īmazon Redshift can now query across databases in a cluster.Īmazon Redshift can now store and process HyperLogLogSketches.Įnhancements to creating external tables for Redshift Spectrum. Support for altering a table column encoding You can now can write Lambda UDFs to enable external tokenization of data. TIME data type stores the time of day without timezone information,Īnd TIMETZ stores the time of day including timezone information You can now create tables with TIME and TIMETZ data types. You can now keep materialized views up-to-date with automatic refresh and query performance can be improved with automatic rewrite. Support for automatic refresh and query rewrite of materialized views You can now create, train, and deploy machine learning (ML) models. You can now define automatic distribution and sort keys. You can now share data across Amazon Redshift clusters. You can now write a federated query to a supported MySQL engine. Support for native JSON and semi-structured data In your Amazon Redshift cluster to create more fine-grained access control policy. You can now grant the privilege to run COPY and UNLOAD commands to specific users and groups Support for fine-grained access control on COPY and UNLOAD commands You can now query data across databases in a cluster. You can now use a recursive common table expression (CTE) in your SQL. Support for hierarchical data queries with recursive CTE You can now share data across AWS accounts. You can now use the COLLATE clause within a CREATE DATABASE statement to specify the default collation. Support for case-insensitive collation with column level overrides You can now run multiple SQL statements or a statement with parameters with the Amazon Redshift Data API. Support for multiple SQL statements or an SQL statement with parameters using the Amazon Redshift Data API You can specify the ENCODE AUTO option for a table to automatically manage compression encoding for all columns in the table. Support for column compression encoding for automatic table optimization You can now use additional spatial functions and 3D and 4D geometry support is added to some functions. ![]() Support for spatial 3D and 4D geometries and new spatial functions ![]()
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