AWS Big Data Blog

In today’s digital world, data is generated by a large number of disparate sources and growing at an exponential rate. Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive […]

This blog post is co-written with Ori Nakar from Imperva. Imperva Cloud WAF protects hundreds of thousands of websites and blocks billions of security events every day. Events and many other security data types are stored in Imperva’s Threat Research Multi-Region data lake. Imperva harnesses data to improve their business outcomes. To enable this transformation […]

AWS Glue interactive sessions allow engineers to build, test, and run data preparation and analytics workloads in an interactive notebook. Interactive sessions provide isolated development environments, take care of the underlying compute cluster, and allow for configuration to stop idling resources. Glue interactive sessions provides default recommended configurations, and also allows users to customize the […]

Large organizations processing huge volumes of data usually store it in Amazon Simple Storage Service (Amazon S3) and query the data to make data-driven business decisions using distributed analytics engines such as Amazon Athena. If you simply run queries without considering the optimal data layout on Amazon S3, it results in a high volume of […]

Using Amazon OpenSearch Service’s vector database capabilities, you can implement semantic search, Retrieval Augmented Generation (RAG) with LLMs, recommendation engines, and search in rich media. Learn how.

Amazon Redshift is a fast, petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all of your data using standard SQL. Tens of thousands of customers today rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the most widely used cloud data warehouse. You can […]

Amazon DynamoDB is a fully managed NoSQL service that delivers single-digit millisecond performance at any scale. It’s used by thousands of customers for mission-critical workloads. Typical use cases for DynamoDB are an ecommerce application handling a high volume of transactions, or a gaming application that needs to maintain scorecards for players and games. In traditional […]

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. It’s common to store the logs generated by customer’s applications and services in various tools. These logs are important for compliance, audits, troubleshooting, security incident responses, meeting security policies, and many other […]

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon Simple Storage Service (Amazon S3) and data sources residing in AWS, on-premises, or other cloud systems using SQL or Python. Athena is built on open-source Trino and Presto engines, and Apache Spark frameworks, with no provisioning or configuration effort […]

With Amazon Managed Streaming for Apache Kafka (Amazon MSK), you can build and run applications that use Apache Kafka to process streaming data. To process streaming data, organizations either use multiple Kafka clusters based on their application groupings, usage scenarios, compliance requirements, and other factors, or a dedicated Kafka cluster for the entire organization. It […]