The most impactful data-driven insights come from getting a full picture of your business and customers. You can only achieve this when you connect data from all your data sources across multiple departments, services, on-premises tools, and third-party applications.
Data integration with AWS makes it easy to connect to and act on all your data, no matter where it lives. With AWS data integration capabilities, you can bring together data from multiple sources; you can transform, operationalize, and manage data to deliver high quality data across your data lakes and data warehouses.
Benefits of Data integration with AWS
Connect data from every source
Simplify data integration pipeline development
Provide tools designed for users of all skillsets
Support all of your workloads
Address data integration challenges with AWS
Data systems are sprawling and siloed
AWS helps you access and integrate data from anywhere you store it, letting your data integration teams focus on high-value activities that maximize the value of your data.
AWS Glue makes it easy to discover, prepare and integrate all your data at any scale. AWS Database Migration Service helps move database and analytics workloads to AWS quickly, securely, and with minimal downtime and zero data loss. Amazon Managed Workflows for Apache Airflow (MWAA) provides secure and highly available managed workflow orchestration for Apache Airflow. AWS Data Exchange connects with third-party data from 300+ data providers and 3,500+ data products.
Data integration can be complex and time-consuming
For complex use cases where you need to transform data, normalize data, check data quality before ingesting data from a raw data store, or reduce table columns, rows, or data size, AWS Glue makes it easier for you to prepare and integrate data.
For common use cases where ETL is regularly repeated, you can use AWS zero-ETL capabilities, which eliminate the need to build and manage ETL pipelines. With AWS zero-ETL capabilities, you can directly ingest streaming data from Amazon Managed Streaming for Apache Kafka to Amazon Redshift, analyze Amazon Aurora data with Amazon Redshift in near real time, and so much more.
Different user skillsets require specific capabilities
Users across the business have varying technical abilities to interact with the data, and may not be able to do so without the right tools.
AWS provides skill-specific interfaces and job-authoring tools for all user types, from developers to business users. AWS Glue Studio automatically generates ETL code, and lets ETL developers and business analysts transform data with a no-code interface. AWS Glue also lets developers and engineers use their preferred IDE, notebook, and processing engines. Amazon Managed Workflows for Apache Airflow enables scientists and engineers to orchestrate end-to-end data pipelines.
Data integration workloads are diverse
AWS provides support for various workloads with no lock-in.
AWS Glue Studio helps you author highly scalable ETL jobs without becoming an Apache Spark expert, and load structured and unstructured data to data warehouses and data lakes. Amazon Managed Streaming for Apache Kafka (MSK) and Amazon Kinesis make it easy to ingest and process streaming data in real-time. Other common workloads include batch data transformation, database replication, data ingestion from SaaS, data sharing among teams, and subscription to third-party data.
Related AWS services and features
AWS Glue – discover, prepare, and integrate all your data at any scale
AWS Q for Data Integration - generative AI-powered AWS Glue capability, enables you to build data integration jobs using natural language.
Amazon Managed Workflows for Apache Airflow – secure and highly available managed workflow orchestration for Apache Airflow
Amazon AppFlow – automate data flows between software as a service (SaaS) and AWS services
Amazon Aurora zero-ETL Integrations with Amazon Redshift – perform near real-time analytics and ML on petabytes of transactional data in Aurora
AWS Database Migration Service – move your database and analytics workflows to AWS quickly, securely, and with minimal downtime and zero data loss
Amazon Athena – analyze petabyte-scale data where it lives with ease and flexibility
Amazon Redshift – best price-performance for cloud data warehousing
AWS Lake Formation – build, manage, and secure data lakes in days
AWS Data Exchange – easily find, subscribe to, and use third-party data in the cloud
AWS Glue Catalog – store, annotate and share metadata in the AWS cloud
Amazon DataZone – unlock data across organizational boundaries with built-in governance