Category: Amazon Redshift

Simplify data replication and ingestion from applications such as Salesforce, SAP, ServiceNow, and Zendesk, to Amazon SageMaker Lakehouse and Amazon Redshift.

The spooky season has come and gone now. While there aren’t any Halloween-themed releases, AWS has celebrated it in big style by having a plethora of exciting releases last week! I think it’s safe to say that we have truly entered the ‘pre’ re:Invent stage as more and more interesting things are being released every […]

Unlock insights instantly with Amazon Redshift’s new zero-ETL integrations for Aurora PostgreSQL and DynamoDB, eliminating complex ETL pipelines.

Near real-time data replication: RDS for MySQL zero-ETL with Redshift streamlines data ingestion with filtering, multiple integrations, and CloudFormation support for customized insights without managing complex pipelines.

Amazon Redshift puts artificial intelligence (AI) at your service to optimize efficiencies and make you more productive with two new capabilities that we are launching in preview today. First, Amazon Redshift Serverless becomes smarter. It scales capacity proactively and automatically along dimensions such as the complexity of your queries, their frequency, the size of the […]

“Data is at the center of every application, process, and business decision,” wrote Swami Sivasubramanian, VP of Database, Analytics, and Machine Learning at AWS, and I couldn’t agree more. A common pattern customers use today is to build data pipelines to move data from Amazon Aurora to Amazon Redshift. These solutions help them gain insights […]

Summer is in full swing here in Seattle and we are spending more time outside and less at the keyboard. Nevertheless, the launch machine is running at full speed and I have plenty to share with you today. Let’s dive in and take a look! Last Week’s Launches Here are some launches that caught my […]

When we talk with customers, we hear that they want to be able to harness insights from data in order to make timely, impactful, and actionable business decisions. A common pattern with data-driven organizations is that they have many different data sources they need to ingest into their analytics systems. This requires them to build […]