Category: Amazon Redshift

This is a guest post by Shimpei Kodama, data engineer at Cookpad Inc. Cookpad is a tech company that builds a community platform where people share recipe ideas and cooking tips. The company’s mission is to “make everyday cooking fun.” It’s one of the largest recipe-sharing platforms in Japan with over 50 million users per […]

General Data Protection Regulation (GDPR) is an important aspect of today’s technology world, and processing data in compliance with GDPR is a necessity for those who implement solutions within the AWS public cloud. One article of GDPR is the “right to erasure” or “right to be forgotten” which may require you to implement a solution […]

This is a guest post by Steven Collings, Senior Data Consultant at Zoopla Zoopla is a property website that enables users to find residential or commercial property to buy or rent in the UK and overseas. Since acquiring Property Software Group and Expert Agent, we also offer a backend software that agents can use to […]

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Customers tell us that they want extremely fast query response times so they can make equally fast decisions. This post presents the recently launched, […]

February 2023 Update: Console access to the AWS Data Pipeline service will be removed on April 30, 2023. On this date, you will no longer be able to access AWS Data Pipeline though the console. You will continue to have access to AWS Data Pipeline through the command line interface and API. Please note that […]

Customers use Amazon Redshift for everything from accelerating existing database environments, to ingesting weblogs for big data analytics. Amazon Redshift is a fully managed, petabyte-scale, massively parallel data warehouse that offers simple operations and high performance. Amazon Redshift provides an open standard JDBC/ODBC driver interface, which allows you to connect your existing business intelligence (BI) tools and reuse existing analytics queries. Amazon Redshift can run any type of data model, from a production transaction system third-normal-form model to star and snowflake schemas, data vault, or simple flat tables. This post takes you through the most common performance-related opportunities when adopting Amazon Redshift and gives you concrete guidance on how to optimize each one. 

This post provides guidance on how to configure Amazon Athena federation with AWS Lambda and Amazon Redshift, while addressing performance considerations to ensure proper use.

This is a guest post by Pradnya Bhandary, Co-Founder and CEO at Bryte Systems. Data can be transformative for an organization. How and where you store your data for analysis and business intelligence is therefore an especially important decision that each organization needs to make. Should you choose an on-premises data warehouse solution or embrace […]

When we look at enterprise data warehousing systems, we receive data in various formats, such as XML, JSON, or CSV. Most third-party system integrations happen through SOAP or REST web services, where the input and output data format is either XML or JSON. When applications deal with CSV or JSON, it becomes fairly simple to […]

One of our favorite things about working on Amazon Redshift, the cloud data warehouse service at AWS, is the inspiring stories from customers about how they’re using data to gain business insights. Many of our recent engagements have been with customers upgrading to the new instance type, Amazon Redshift RA3 with managed storage. In this […]