Category: Analytics

You can use the Amazon EMR Steps API to submit Apache Hive, Apache Spark, and others types of applications to an EMR cluster. You can invoke the Steps API using Apache Airflow, AWS Steps Functions, the AWS Command Line Interface (AWS CLI), all the AWS SDKs, and the AWS Management Console. Jobs submitted with the […]

Many organizations build data lakes on Amazon Simple Storage Service (Amazon S3) using a modern architecture for a scalable and cost-effective solution. Open-source storage formats like Parquet and Avro are commonly used, and data is stored in these formats as immutable files. As the data lake is expanded to additional use cases, there are still […]

AWS Glue includes crawlers, a capability that make discovering datasets simpler by scanning data in Amazon Simple Storage Service (Amazon S3) and relational databases, extracting their schema, and automatically populating the AWS Glue Data Catalog, which keeps the metadata current. This reduces the time to insight by making newly ingested data quickly available for analysis […]

AWS Glue now offers integration with Git, an open-source version control system widely used across the developer community. Thanks to this integration, you can incorporate your existing DevOps practices on AWS Glue jobs. AWS Glue is a serverless data integration service that helps you create jobs based on Apache Spark or Python to perform extract, […]

Customers tell us they want to have stronger performance and lower costs for their data analytics applications and workloads. Customers also want to use AWS as a platform that hosts managed versions of their favorite open-source projects, which will frequently adopt the latest features from the open-source communities. With Amazon Athena engine version 3, we […]

Today, many companies are building real-time applications to improve their customer experience and get immediate insights from their data before it loses its value. As the result, companies have been facing increasing demand to provide data streaming services such as Apache Kafka for developers. To meet this demand, companies typically start with a small- or […]

In modern data architectures, it’s common to store data in multiple data sources. However, organizations embracing this approach still need insights from their data and require technologies that help them break down data silos. Amazon Athena is an interactive query service that makes it easy to analyze structured, unstructured, and semi-structured data stored in Amazon […]

To build a data lake on AWS, a common data ingestion pattern is to use AWS Glue jobs to perform extract, transform, and load (ETL) data from relational databases to Amazon Simple Storage Service (Amazon S3). A project often involves extracting hundreds of tables from source databases to the data lake raw layer. And for […]

In today’s world with technology modernization, the need for near-real-time streaming use cases has increased exponentially. Many customers are continuously consuming data from different sources, including databases, applications, IoT devices, and sensors. Organizations may need to ingest that streaming data into data lakes built on Amazon Simple Storage Service (Amazon S3). You may also need […]

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. Stream data processing allows you to act on data in real time. Real-time data analytics can help you have on-time and optimized responses while improving overall customer […]