Simplify your data integration with Zero-ETL

Zero-ETL in Amazon OpenSearch Service helps you to simplify your data integration process, enables real-time data analysis, reduces infrastructure complexity, and provides a scalable and cost-effective solution for ingesting and analyzing data from various AWS data sources.

Zero-ETL Amazon S3 integration

Streamline your data analytics process by eliminating the need for complex ETL pipelines when working with your Amazon S3 data lake, reducing operational complexity and costs. Learn more >>

Zero-ETL DynamoDB integration

Eliminate the need for custom code or complex data pipelines when using advanced search capabilities such as full-text and vector search by leveraging the zero-ETL integration between Amazon OpenSearch Service and Amazon DynamoDB, reducing operational burden and costs associated with keeping data in sync. Learn More>>

Zero-ETL DocumentDB integration

Utilize advanced search capabilities (such as fuzzy search, semantic search, and more) on your Amazon DocumentDB documents using the OpenSearch API. With this integration, you can also uniquely search across collections and other non-English languages. Learn More>>

Streamline data ingestion across diverse sources

Amazon OpenSearch Service simplifies the data ingestion process, allowing you to transfer data from various sources into your OpenSearch cluster. Whether you're dealing with structured databases, unstructured log files, or real-time streaming data, our connectors enable you to consolidate your data into a unified platform offering scalability and cost-effectiveness. 

Amazon OpenSearch Ingestion

Collect, transform, and route data seamlessly to your OpenSearch Service domains. With its serverless architecture, OpenSearch Ingestion Service automatically scales to meet the processing needs of your ingest workloads, ensuring a smooth and efficient data pipeline. Learn more >>

Amazon Kinesis Data Firehose ingestion

Convert raw streaming data from various sources into the required formats for your Elasticsearch or OpenSearch index, and load it seamlessly to Amazon OpenSearch Service without building custom data processing pipelines. Use the pre-built Lambda blueprints in Amazon Kinesis Firehose for converting common data sources like Apache and system logs into JSON and CSV formats, and offers automatic job retries and raw data backup capabilities. Learn more >>

Logstash ingestion

Deploy Logstash on Amazon EC2 and set up your Amazon OpenSearch Service domain as the backend store for all logs coming through your Logstash implementation. Logstash supports a library of pre-built filters to easily perform common transformations such as parsing unstructured log data into structured data through pattern-matching; renaming, removing, replacing, and modifying fields in your data records; and aggregating metrics. Learn more >>

Amazon CloudWatch Logs ingestion

Stream data to your Amazon OpenSearch Service domain in near real-time through an Amazon CloudWatch Logs. This integration is convenient if you are already using CloudWatch Logs to collect log data and would like to share that data with your Amazon OpenSearch Service users.  Learn more >>

Amazon IoT ingestion

Simplify device-to-cloud connectivity and enable secure data exchange between IoT devices, such as consumer appliances and cloud applications. Using the AWS Management Console you can configure AWS IoT to load the data directly to Amazon OpenSearch Service, enabling you to provide your customers near real-time access to IoT data and metrics. Learn More >>

Next steps

OpenSearch includes certain Apache-licensed Elasticsearch code from Elasticsearch B.V. and other source code. Elasticsearch B.V. is not the source of that other source code. ELASTICSEARCH is a registered trademark of Elasticsearch B.V.

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