AWS Big Data Blog

Many organizations are establishing enterprise data warehouses, data lakes, or a modern data architecture on AWS to build data-driven products. As the organization grows, the number of publishers and subscribers to data and the volume of data keeps increasing. Additionally, different varieties of datasets are introduced (structured, semistructured, and unstructured). This can lead to metadata […]

This post is co-written with Dr. Quan Hoang Nguyen, CTO at Fantom Foundation. Here at Fantom Foundation (Fantom), we have developed a high performance, highly scalable, and secure smart contract platform. It’s designed to overcome limitations of the previous generation of blockchain platforms. The Fantom platform is permissionless, decentralized, and open source. The majority of […]

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 show how to use MSK Connect for MirrorMaker 2 deployment with AWS Identity and Access Management (IAM) authentication. We create an MSK Connect […]

As the industry grows with more data volume, big data analytics is becoming a common requirement in data analytics and machine learning (ML) use cases. Data comes from many different sources in structured, semi-structured, and unstructured formats. For semi-structured data, one of the most common lightweight file formats is JSON. However, due to the complex […]

Amazon Redshift Serverless makes it simple to run and scale analytics without having to manage the instance type, instance size, lifecycle management, pausing, resuming, and so on. It automatically provisions and intelligently scales data warehouse compute capacity to deliver fast performance for even the most demanding and unpredictable workloads, and you pay only for what […]

In September 2017, during the annual Splunk.conf, Splunk and AWS jointly announced Amazon Kinesis Data Firehose integration to support Splunk Enterprise and Splunk Cloud as a delivery destination. This native integration between Splunk Enterprise, Splunk Cloud, and Kinesis Data Firehose is designed to make AWS data ingestion setup seamless, while offering a secure and fault-tolerant […]

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, […]