Category: Analytics

The AWS Well-Architected Data Analytics Lens provides a set of guiding principles for analytics applications on AWS. One of the best practices it talks about is build a central Data Catalog to store, share, and track metadata changes. AWS Glue provides a Data Catalog to fulfill this requirement. AWS Glue also provides crawlers that automatically […]

Apache Hudi is an open-source transactional data lake framework that greatly simplifies incremental data processing and data pipeline development. It does this by providing transaction support and record-level insert, update, and delete capabilities on data lakes on Amazon Simple Storage Service (Amazon S3) or Apache HDFS. Apache Hudi is integrated with open-source big data analytics […]

This blog post was last reviewed and updated September 2022 with OldGenJVMMemoryPressure, MasterOldGenJVMMemoryPressure and WarmOldGenJVMMemoryPressure metrics to trace usage of old gen.  Amazon OpenSearch Service is a managed service that makes it easy to secure, deploy, and operate OpenSearch and legacy Elasticsearch clusters at scale. In the latest service software release of Amazon OpenSearch Service, […]

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 […]

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 Kinesis Data Analytics makes it easy to transform and analyze streaming data and gain actionable insights in real time with Apache Flink. Apache Flink is an […]

Our customers use Apache Hive on Amazon EMR for large-scale data analytics and extract, transform, and load (ETL) jobs. Amazon EMR Hive uses Apache Tez as the default job execution engine, which creates Directed Acyclic Graphs (DAGs) to process data. Each DAG can contain multiple vertices from which tasks are created to run the application […]

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 […]

Amazon Athena is a serverless interactive query service that makes it easy to analyze data in Amazon Simple Storage Service (Amazon S3) using standard SQL, and you only pay for the amount of data scanned by your queries. If you use SQL to analyze your business on a daily basis, you may find yourself repeatedly […]

Many customers already manage user identities through identity providers (IdPs) for single sign-on access. With an IdP such as Active Directory Federation Services (AD FS), you can set up federated access to Amazon Redshift clusters as a mechanism to control permissions for the database objects by business groups. This provides a seamless user experience, and centralizes the governance […]

This is the fifth in a series of posts. We’re excited to share dozens of new features to automate your schema conversion; preserve your investment in existing scripts, reports, and applications; accelerate query performance; and potentially simplify your migrations from legacy data warehouses to Amazon Redshift. Check out the all the posts in this series: […]