AWS Big Data Blog

Category: Amazon OpenSearch Service

Build a decentralized semantic search engine on heterogeneous data stores using autonomous agents

In this post, we show how to build a Q&A bot with RAG (Retrieval Augmented Generation). RAG uses data sources like Amazon Redshift and Amazon OpenSearch Service to retrieve documents that augment the LLM prompt. For getting data from Amazon Redshift, we use the Anthropic Claude 2.0 on Amazon Bedrock, summarizing the final response based on pre-defined prompt template libraries from LangChain. To get data from Amazon OpenSearch Service, we chunk, and convert the source data chunks to vectors using Amazon Titan Text Embeddings model.

Introducing blueprint discovery and other UI enhancements for Amazon OpenSearch Ingestion

Amazon OpenSearch Ingestion is a fully managed serverless pipeline that allows you to ingest, filter, transform, enrich, and route data to an Amazon OpenSearch Service domain or Amazon OpenSearch Serverless collection. OpenSearch Ingestion is capable of ingesting data from a wide variety of sources and has a rich ecosystem of built-in processors to take care […]

Overview of the solution

AVB accelerates search in LINQ with Amazon OpenSearch Service

AVB Marketing delivers custom digital solutions for their members across a wide range of products. LINQ, AVB’s proprietary product information management system, empowers their appliance, consumer electronics, and furniture retailer members to streamline the management of their product catalog. In this post, we share how AVB reduced their average search time from 3 seconds to 300 milliseconds in LINQ by adopting Amazon OpenSearch Service while processing 14.5 million record updates daily.

Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service is now available

Today, we are announcing the general availability of Amazon DocumentDB (with MongoDB compatibility) zero-ETL integration with Amazon OpenSearch Service. Amazon DocumentDB provides native text search and vector search capabilities. With Amazon OpenSearch Service, you can perform advanced search analytics, such as fuzzy search, synonym search, cross-collection search, and multilingual search, on Amazon DocumentDB data. Zero-ETL […]

Analyze more demanding as well as larger time series workloads with Amazon OpenSearch Serverless 

In today’s data-driven landscape, managing and analyzing vast amounts of data, especially logs, is crucial for organizations to derive insights and make informed decisions. However, handling this data efficiently presents a significant challenge, prompting organizations to seek scalable solutions without the complexity of infrastructure management. Amazon OpenSearch Serverless lets you run OpenSearch in the AWS […]

Amazon OpenSearch Service Under the Hood : OpenSearch Optimized Instances(OR1)

Amazon OpenSearch Service recently introduced the OpenSearch Optimized Instance family (OR1), which delivers up to 30% price-performance improvement over existing memory optimized instances in internal benchmarks, and uses Amazon Simple Storage Service (Amazon S3) to provide 11 9s of durability. With this new instance family, OpenSearch Service uses OpenSearch innovation and AWS technologies to reimagine […]

Simplify your query management with search templates in Amazon OpenSearch Service

Amazon OpenSearch Service is an Apache-2.0-licensed distributed search and analytics suite offered by AWS. This fully managed service allows organizations to secure data, perform keyword and semantic search, analyze logs, alert on anomalies, explore interactive log analytics, implement real-time application monitoring, and gain a more profound understanding of their information landscape. OpenSearch Service provides the […]

Amazon OpenSearch H2 2023 in review

2023 was been a busy year for Amazon OpenSearch Service! Learn more about the releases that OpenSearch Service launched in the first half of 2023. In the second half of 2023, OpenSearch Service added the support of two new OpenSearch versions: 2.9 and 2.11 These two versions introduce new features in the search space, machine […]

Build a RAG data ingestion pipeline for large-scale ML workloads

For building any generative AI application, enriching the large language models (LLMs) with new data is imperative. This is where the Retrieval Augmented Generation (RAG) technique comes in. RAG is a machine learning (ML) architecture that uses external documents (like Wikipedia) to augment its knowledge and achieve state-of-the-art results on knowledge-intensive tasks. For ingesting these […]