AWS Big Data Blog

Category: Database

Migrate a large data warehouse from Greenplum to Amazon Redshift using AWS SCT – Part 2

In this second post of a multi-part series, we share best practices for choosing the optimal Amazon Redshift cluster, data architecture, converting stored procedures, compatible functions and queries widely used for SQL conversions, and recommendations for optimizing the length of data types for table columns. You can check out the first post of this series […]

Migrate a large data warehouse from Greenplum to Amazon Redshift using AWS SCT – Part 1

A data warehouse collects and consolidates data from various sources within your organization. It’s used as a centralized data repository for analytics and business intelligence. When working with on-premises legacy data warehouses, scaling the size of your data warehouse or improving performance can mean purchasing new hardware or adding more powerful hardware. This is often […]

How William Hill migrated NoSQL workloads at scale to Amazon Keyspaces

Social gaming and online sports betting are competitive environments. The game must be able to handle large volumes of unpredictable traffic while simultaneously promising zero downtime. In this domain, user retention is no longer just desirable, it’s critical. William Hill is a global online gambling company based in London, England, and it is the founding […]

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Sink Amazon Kinesis Data Analytics Apache Flink output to Amazon Keyspaces using Apache Cassandra Connector

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Amazon Keyspaces (for Apache Cassandra) is a scalable, highly available, and managed Apache Cassandra–compatible database service. With Amazon Keyspaces you don’t have to provision, patch, or manage […]

Accelerate Amazon DynamoDB data access in AWS Glue jobs using the new AWS Glue DynamoDB Export connector

Jan 2024: This post was reviewed and updated for accuracy. Modern data architectures encourage the integration of data lakes, data warehouses, and purpose-built data stores, enabling unified governance and easy data movement. With a modern data architecture on AWS, you can store data in a data lake and use a ring of purpose-built data services […]

Stream change data to Amazon Kinesis Data Streams with AWS DMS

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. In this post, we discuss how to use AWS Database Migration Service (AWS DMS) native change data capture (CDC) capabilities to stream changes into Amazon Kinesis Data […]

Optimize Federated Query Performance using EXPLAIN and EXPLAIN ANALYZE in Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon Simple Storage Service (Amazon S3) using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. In 2019, Athena added support for federated queries to run SQL […]

Accelerate Snowflake to Amazon Redshift migration using AWS Schema Conversion Tool

July 2023: This post was reviewed for accuracy. Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can start with just a few hundred gigabytes of data and scale to a petabyte or more. This enables you to use your data to acquire new insights for your business and customers. […]

Solution Architecture

Build data lineage for data lakes using AWS Glue, Amazon Neptune, and Spline

Data lineage is one of the most critical components of a data governance strategy for data lakes. Data lineage helps ensure that accurate, complete and trustworthy data is being used to drive business decisions. While a data catalog provides metadata management features and search capabilities, data lineage shows the full context of your data by […]

What to consider when migrating data warehouse to Amazon Redshift

Customers are migrating data warehouses to Amazon Redshift because it’s fast, scalable, and cost-effective. However, data warehouse migration projects can be complex and challenging. In this post, I help you understand the common drivers of data warehouse migration, migration strategies, and what tools and services are available to assist with your migration project. Let’s first […]