AWS Big Data Blog
Category: Amazon Redshift
Accelerate orchestration of an ELT process using AWS Step Functions and Amazon Redshift Data API
Extract, Load, and Transform (ELT) is a modern design strategy where raw data is first loaded into the data warehouse and then transformed with familiar Structured Query Language (SQL) semantics leveraging the power of massively parallel processing (MPP) architecture of the data warehouse. When you use an ELT pattern, you can also use your existing […]
Run a popular benchmark on Amazon Redshift Serverless easily with AWS Data Exchange
Amazon Redshift is a fast, easy, secure, and economical cloud data warehousing service designed for analytics. AWS announced Amazon Redshift Serverless general availability in July 2022, providing an easier experience to operate Amazon Redshift. Amazon Redshift Serverless makes it simple to run and scale analytics without having to manage your data warehouse infrastructure. Amazon Redshift […]
Code conversion from Greenplum to Amazon Redshift: Handling arrays, dates, and regular expressions
Amazon Redshift is a fully managed service for data lakes, data analytics, and data warehouses for startups, medium enterprises, and large enterprises. Amazon Redshift is used by tens of thousands of businesses around the globe for modernizing their data analytics platform. Greenplum is an open-source, massively parallel database used for analytics, mostly for on-premises infrastructure. […]
Near-real-time fraud detection using Amazon Redshift Streaming Ingestion with Amazon Kinesis Data Streams and Amazon Redshift ML
The importance of data warehouses and analytics performed on data warehouse platforms has been increasing steadily over the years, with many businesses coming to rely on these systems as mission-critical for both short-term operational decision-making and long-term strategic planning. Traditionally, data warehouses are refreshed in batch cycles, for example, monthly, weekly, or daily, so that […]
How to get best price performance from your Amazon Redshift Data Sharing deployment
Amazon Redshift is a fast, scalable, secure, and fully-managed data warehouse that enables you to analyze all of your data using standard SQL easily and cost-effectively. Amazon Redshift Data Sharing allows customers to securely share live, transactionally consistent data in one Amazon Redshift cluster with another Amazon Redshift cluster across accounts and regions without needing to […]
Migrate Google BigQuery to Amazon Redshift using AWS Schema Conversion tool (SCT)
Amazon Redshift is a fast, fully-managed, petabyte scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. Using Amazon Redshift Serverless and Query Editor v2, you can load and query large datasets in just a few clicks and pay only for what you use. The decoupled compute and […]
Create, Train and Deploy Multi Layer Perceptron (MLP) models using Amazon Redshift ML
Amazon Redshift is a fully managed and petabyte-scale cloud data warehouse which is being used by tens of thousands of customers to process exabytes of data every day to power their analytics workloads. Amazon Redshift comes with a feature called Amazon Redshift ML which puts the power of machine learning in the hands of every […]
Scale read and write workloads with Amazon Redshift
Amazon Redshift is a fast, fully managed, petabyte-scale cloud data warehouse that enables you to analyze large datasets using standard SQL. The concurrency scaling feature in Amazon Redshift automatically adds and removes capacity by adding concurrency scaling to handle demands from thousands of concurrent users, thereby providing consistent SLAs for unpredictable and spiky workloads such […]
Migrate a large data warehouse from Greenplum to Amazon Redshift using AWS SCT – Part 3
In this third post of a multi-part series, we explore some of the edge cases in migrating a large data warehouse from Greenplum to Amazon Redshift using AWS Schema Conversion Tool (AWS SCT) and how to handle these challenges. Challenges include how best to use virtual partitioning, edge cases for numeric and character fields, and […]
How Blueshift integrated their customer data environment with Amazon Redshift to unify and activate customer data for marketing
This post was co-written with Vijay Chitoor, Co-Founder & CEO, and Mehul Shah, Co-Founder and CTO from the Blueshift team, as the lead authors. Blueshift is a San Francisco-based startup that helps marketers deliver exceptional customer experiences on every channel, delivering relevant personalized marketing. Blueshift’s SmartHub Customer Data Platform (CDP) empowers marketing teams to activate […]