Category: Storage

Many customers have taken advantage of the numerous benefits of running Apache HBase on Amazon S3 for data storage, including lower costs, data durability, and easier scalability. Customers such as FINRA have lowered their costs by 60% by moving to an HBase on S3 architecture along with the numerous operational benefits that come with decoupling […]

One of the great benefits of Amazon S3 is the ability to host, share, or consume public data sets. This provides transparency into data to which an external data scientist or developer might not normally have access. By exposing the data to the public, you can glean many insights that would have been difficult with […]

When Amazon S3 analytics was released in November 2016, it gave you the ability to analyze storage access patterns and transition the right data to the right storage class. You could also manually export the data to an S3 bucket to analyze, using the business intelligence tool of your choice, and gather deeper insights on usage and growth patterns. This helped you reduce storage costs while optimizing performance based on usage patterns. With today’s update, you can quickly and easily gain those deeper insights and benefits by analyzing and visualizing S3 analytics data in Amazon QuickSight. It takes just a single click from the S3 console, without the need for manual exports or additional data preparation.

Although it’s common for Amazon EMR customers to process data directly in Amazon S3, there are occasions where you might want to copy data from S3 to the Hadoop Distributed File System (HDFS) on your Amazon EMR cluster. Additionally, you might have a use case that requires moving large amounts of data between buckets or regions. In these use cases, large datasets are too big for a simple copy operation.

Starting with Amazon EMR 5.2.0, you have the option to run Apache HBase on Amazon S3. Running HBase on S3 gives you several added benefits, including lower costs, data durability, and easier scalability. HBase provides several options that you can use to migrate and back up HBase tables. The steps to migrate to HBase on […]

Sometimes, data to be analyzed is spread across buckets owned by different accounts. In order to ensure data security, appropriate credentials management needs to be in place. This is especially true for large enterprises storing data in different Amazon S3 buckets for different departments. For example, a customer service department may need access to data […]

All software developers strive to build products that are functional, robust, and bug-free, but video game developers have an extra challenge: they must also create a product that entertains. When designing a game, developers must consider how the various elements—such as characters, story, environment, and mechanics—will fit together and, more importantly, how players will interact […]

May 2022: This post was reviewed for messaging and accuracy. Amazon Athena is an interactive query service that makes it easy to analyze data directly from Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to set up or manage and you can start analyzing your data immediately. You don’t even […]

John Hitchingham is Director of Performance Engineering at FINRA The Financial Industry Regulatory Authority (FINRA) is a private sector regulator responsible for analyzing 99% of the equities and 65% of the option activity in the US. In order to look for fraud, market manipulation, insider trading, and abuse, FINRA’s technology group has developed a robust […]

In today’s blog post, I will discuss how to optimize Amazon S3 for an architecture commonly used to enable genomic data analyses. This optimization is important to my work in genomics because, as genome sequencing continues to drop in price, the rate at which data becomes available is accelerating.