AWS Big Data Blog

Category: Analytics

Stream CDC into an Amazon S3 data lake in Parquet format with AWS DMS

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. Most organizations generate data in real time and ever-increasing volumes. Data is captured from a variety of sources, such as transactional and reporting databases, application logs, customer-facing websites, and external feeds. Companies […]

Amazon EMR supports Apache Hive ACID transactions

December 2022: The best practice of using EMRFS consistent in this blog post is now obsolete as Amazon S3 has supported strong read-after-write consistency since December, 2020.  Apache Hive is an open-source data warehouse package that runs on top of an Apache Hadoop cluster. You can use Hive for batch processing and large-scale data analysis. […]

Fast and predictable performance with serverless compilation using Amazon Redshift

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, […]

Power data analytics, monitoring, and search use cases with the Open Distro for Elasticsearch SQL Engine on Amazon ES

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. Amazon OpenSearch Service is a popular choice for log analytics, search, real-time application monitoring, clickstream analysis, and more. One commonality among these use cases is the need to write and run queries to obtain search results at lightning speed. However, […]

How Aruba Networks built a cost analysis solution using AWS Glue, Amazon Redshift, and Amazon QuickSight

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 […]

Build a self-service environment for each line of business using Amazon EMR and AWS Service Catalog

Enterprises often want to centralize governance and compliance requirements, and provide a common set of policies on how Amazon EMR instances should be set up. You can use AWS Service Catalog to centrally manage commonly deployed Amazon EMR cluster configurations, and this helps you achieve consistent governance and meet your compliance requirements, while at the […]

Top 10 performance tuning techniques for Amazon Redshift

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.