Amazon Redshift ML Is Now Generally Available – Use SQL to Create Machine Learning Models and Make Predictions from Your Data

With Amazon Redshift, you can use SQL to query and combine exabytes of structured and semi-structured data across your data warehouse, operational databases, and data lake. Now that AQUA (Advanced Query Accelerator) is generally available, you can improve the performance of your queries by up to 10 times with no additional costs and no code Read more about Amazon Redshift ML Is Now Generally Available – Use SQL to Create Machine Learning Models and Make Predictions from Your Data[…]

AQUA (Advanced Query Accelerator) – A Speed Boost for Your Amazon Redshift Queries

Amazon Redshift already provides up to 3x better price-performance at any scale than any other cloud data warehouse. We do this by designing our own hardware and by using Machine Learning (ML). For example, we launched the SSD-based RA3 nodes for Amazon Redshift at the end of 2019 (Amazon Redshift Update – Next-Generation Compute Instances Read more about AQUA (Advanced Query Accelerator) – A Speed Boost for Your Amazon Redshift Queries[…]

Amazon Redshift update – ra3.4xlarge nodes

Since we launched Amazon Redshift as a cloud data warehouse service more than seven years ago, tens of thousands of customers built their workloads using it. We are always listening to your feedback and, in December last year, we announced our 3rd generation RA3 node type providing you the ability to scale compute and storage Read more about Amazon Redshift update – ra3.4xlarge nodes[…]

Materialize your Amazon Redshift Views to Speed Up Query Execution

At AWS, we take pride in building state of the art virtualization technologies to simplify the management and access to cloud services such as networks, computing resources or object storage. In a Relational Database Management Systems (RDBMS), a view is virtualization applied to tables : it is a virtual table representing the result of a Read more about Materialize your Amazon Redshift Views to Speed Up Query Execution[…]

Using Spatial Data with Amazon Redshift

Today, Amazon Redshift announced support for a new native data type called GEOMETRY. This new type enables ingestion, storage, and queries against two-dimensional geographic data, together with the ability to apply spatial functions to that data. Geographic data (also known as georeferenced data) refers to data that has some association with a location relative to Read more about Using Spatial Data with Amazon Redshift[…]

AWS Lake Formation – Now Generally Available

As soon as companies started to have data in digital format, it was possible for them to build a data warehouse, collecting data from their operational systems, such as Customer relationship management (CRM) and Enterprise resource planning (ERP) systems, and use this information to support their business decisions. The reduction in costs of storage, together Read more about AWS Lake Formation – Now Generally Available[…]

New – Concurrency Scaling for Amazon Redshift – Peak Performance at All Times

Amazon Redshift is a data warehouse that can expand to exabyte-scale. Today, tens of thousands of AWS customers (including NTT DOCOMO, Finra, and Johnson & Johnson) use Redshift to run mission-critical BI dashboards, analyze real-time streaming data, and run predictive analytics jobs. A challenge arises when the number of concurrent queries grows at peak times. Read more about New – Concurrency Scaling for Amazon Redshift – Peak Performance at All Times[…]