All news with #amazon redshift tag

AWS Glue Adds Zero-ETL Support for More SAP Entities

🔄 AWS Glue now provides full snapshot and incremental zero-ETL ingestion for additional SAP entities. The update adds snapshot ingestion for entities without deletion tracking and timestamp-based incremental loads for non-ODP systems, extending existing ODP support. Organizations can ingest SAP data directly into Amazon Redshift or the lakehouse architecture used by Amazon SageMaker, reducing engineering effort and operational complexity. This feature is available in all Regions where AWS Glue zero-ETL is offered.

Amazon Redshift JIT ANALYZE for Apache Iceberg tables

📈 Amazon Redshift now supports Just‑In‑Time (JIT) ANALYZE for Apache Iceberg tables, automatically collecting table‑ and column‑level statistics during query execution. The feature uses intelligent heuristics and lightweight sketch data structures to determine when runtime statistics will improve optimizer decisions and to build high‑quality statistics on the fly. JIT ANALYZE is generally available in all AWS regions with Redshift and requires no configuration changes to begin improving query plans and performance.

Amazon Redshift Adds SUPER Type for Case-Insensitive DBs

🧩 Amazon Redshift now supports the SUPER data type in databases configured with case-insensitive collation, enabling analytics on semi-structured and nested data alongside structured SQL types. Using PartiQL, users can query JSON and mixed data without additional normalization. The COLLATE function lets you explicitly control case sensitivity for SUPER columns. This capability is available in all AWS Regions, including AWS GovCloud (US).

Amazon Redshift Adds Apache Iceberg Write Support (GA)

🔔 Amazon Redshift now supports write operations to Apache Iceberg tables in general availability, enabling SQL DDL and DML including CREATE, SHOW, DROP, and INSERT for append-only workloads. Customers can execute concurrent read and write queries against Iceberg tables cataloged in AWS Glue Data Catalog while benefiting from transactional consistency and schema and partition evolution support. The capability is available in all regions where Amazon Redshift is offered.

Amazon Redshift Serverless Now in Osaka and Malaysia

🚀 Amazon Redshift Serverless is now generally available in the AWS Asia Pacific (Osaka) and Asia Pacific (Malaysia) regions. It enables data analysts, developers, and data scientists to run and scale analytics without provisioning or managing clusters by automatically provisioning and intelligently scaling compute capacity. You pay per-second for compute and can query data in-place from Amazon S3 (including Apache Parquet), use Redshift data shares, restore provisioned snapshots, or work through the Query Editor V2 or existing BI tools.

DynamoDB Zero-ETL Integration with Redshift in Taipei

🔁 The Amazon DynamoDB zero-ETL integration with Amazon Redshift is now available in the Asia Pacific (Taipei) region, enabling analytics on production DynamoDB tables without impacting operational workloads. Customers can run high-performance SQL, leverage built-in ML and Spark integrations, and use materialized views with automatic incremental refresh and data sharing. History mode provides built-in support for analyzing historical data and building Type 2 Slowly Changing Dimension (SCD 2) tables without custom ETL code.

Amazon Redshift Auto-Copy Expands to Four AWS Regions

📥 Amazon Redshift Auto-Copy is now available in Asia Pacific (Malaysia), Asia Pacific (Thailand), Mexico (Central), and Asia Pacific (Taipei). The feature lets you configure an integration to continuously detect and load new files from a specified Amazon S3 prefix into Redshift tables without requiring custom COPY pipelines or external tooling. Auto-Copy records previously loaded files to prevent duplicate ingestion and exposes job status and metrics via Redshift system tables for monitoring and troubleshooting.

Amazon RDS for Oracle Zero-ETL Integration in 8 Regions

⚡ Amazon RDS for Oracle now offers zero-ETL integration with Amazon Redshift in eight additional AWS Regions, enabling near real-time analytics and ML on transactional data without building ETL pipelines. Data written to an RDS for Oracle instance is replicated to Redshift within seconds. Administrators can configure integrations via Console, API, CLI, or CloudFormation, select specific PDBs and tables, and must use Oracle Database 19c.

Amazon RDS MySQL and PostgreSQL Zero-ETL to Redshift

⚡Amazon RDS for MySQL and Amazon RDS for PostgreSQL now support zero-ETL integrations with Amazon Redshift in eight additional regions. Data written to RDS is replicated to Redshift within seconds, enabling near real-time analytics and ML on transactional datasets. You can create multiple integrations per database, apply per-integration filtering to include or exclude specific databases and tables, and automate deployment with AWS CloudFormation.

Amazon Redshift Serverless Lowers Base Capacity to 8 RPUs

⚙️ Amazon Redshift Serverless now offers a reduced minimum base capacity of 8 Redshift Processing Units (RPUs) in the AWS Asia Pacific (Seoul) and Canada (Central) regions. Each RPU provides 16 GB of memory and billing remains per-second for RPU-hours; the prior minimum was 32 RPUs. Capacity can be adjusted in 8-RPU increments, making Redshift Serverless more cost-effective and flexible for small production, test, and development workloads.

Amazon Redshift Concurrency Scaling Adds More Regions

🚀 Amazon Redshift Concurrency Scaling is now available in ten additional AWS regions, including Africa (Cape Town), several Asia Pacific locations, Europe (Milan), Middle East (Bahrain), Mexico (Central) and AWS GovCloud (US‑West). The feature elastically adds query processing capacity in seconds to maintain fast performance for thousands of concurrent users and hundreds of simultaneous queries. Customers with an active Redshift cluster earn up to one hour of free Concurrency Scaling credits and can control allocation, set cluster limits, and monitor usage through Amazon CloudWatch; enable it by setting the Concurrency Scaling Mode to Auto in the AWS Management Console.

Amazon Redshift Serverless Now Available in Taipei

🚀 Amazon Redshift Serverless is now generally available in the AWS Asia Pacific (Taipei) region, enabling analysts, developers, and data scientists to run and scale analytics without provisioning or managing clusters. The service automatically provisions and intelligently scales compute, with per-second billing for workload duration. Users can query data via Query Editor V2 or existing BI tools, load data from Amazon S3, restore snapshots, and directly query open formats like Apache Parquet, while benefiting from unified billing across data sources.

Amazon Redshift Multidimensional Data Layouts GA for Queries

🚀 Amazon Redshift announces general availability of Multidimensional Data Layouts (MDDL), a dynamic sorting feature that reorganizes data according to actual query filters to accelerate analytics. MDDL creates a multidimensional virtual sort key that co-locates rows typically accessed together, enabling block-level and predicate-column skipping during execution. For tables using the default AUTO sort key, Redshift analyzes query history and automatically selects MDDL or an optimal single-column sort key based on expected benefits. AWS reports up to 10x end-to-end performance improvements for workloads with repetitive filters; MDDL is available in all AWS commercial regions.

Amazon Redshift Serverless Available in Milan, Cape Town

🚀 Amazon Redshift Serverless is now generally available in the AWS Europe (Milan) and Africa (Cape Town) regions. With Redshift Serverless, users—data analysts, developers, and data scientists—can run analytics without provisioning or managing clusters, benefiting from automatic provisioning, intelligent scaling, and per-second compute billing. You can query data via Query Editor V2 or existing BI tools, load data from Amazon S3 (including Apache Parquet), use Redshift data shares, restore provisioned snapshots, and take advantage of unified billing for queries across these sources.