A managed big data platform that simplifies the processing and analysis of large datasets using popular frameworks such as Apache Hadoop, Spark, and Hive. It enables distributed processing and supports various data processing workloads.
A server less interactive query service that allows you to analyze data directly from Amazon S3 using standard SQL queries. It enables ad-hoc querying of large-scale datasets without the need for infrastructure provisioning or data movement.
A fully managed data warehousing service that provides fast and scalable analysis of large data sets. It allows you to run complex analytical queries across your data warehouse, making it suitable for business intelligence, reporting, and data analytics.
A fully managed extract, transform, and load (ETL) service that helps prepare and transform data for analysis. It automates the discovery, cataloging, and transformation of data, making it easier to integrate and cleanse data from various sources.
A real-time data streaming service that enables the collection, processing, and analysis of streaming data at scale. It allows you to ingest and process large volumes of data in real-time from various sources, making it suitable for use cases like IoT data, click stream analysis, and log processing.
An orchestration service that enables you to schedule and automate the movement and transformation of data between different AWS services and on-premises systems. It helps create data pipelines for ETL, data migration, and data synchronization workflows.
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