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Introducing Point in Time queries and SQL/PPL support in Amazon OpenSearch Serverless
- Amazon OpenSearch Serverless now supports Point in Time (PIT) search, Piped Processing Language (PPL) and Structured Query Language (SQL).
- PIT search lets you run different queries against a dataset that’s fixed in time. With PIT, you can query against a state of your dataset and maintains a stable sort.
- PIT search provides superior capabilities and performance because it isn’t bound to a query and supports consistent pagination.
- Using PIT involves three steps: Create a PIT, run search queries with a PIT ID and use the search_after parameter for the next page of results, and close the PIT.
- SQL and PPL give new ways to query data and provide flexibility to use format that works best for you. In addition to DSL, you can extract insights out of OpenSearch Serverless using the familiar SQL query syntax.
- SQL supports complex queries like semi-structured data, set operations, sub-queries with limited joins while PPL queries work by sending queries to the SQL plugin.
- OpenSearch Serverless is a search and analytics engine that enables you to store, search, and analyze large volumes of data while reducing the burden of manual infrastructure provisioning and scaling.
- The vector engine for OpenSearch Serverless makes it easy to build modern machine learning (ML) augmented search experiences and generative artificial intelligence (generative AI) applications without managing underlying vector database infrastructure.
- Keep in mind some limitations when using PIT search and SQL/PPL support. For example, search slicing is not supported in OpenSearch Serverless and the total number of open PITs is restricted to 300 per collection that shares the same AWS KMS key.
- Amazon OpenSearch Serverless is a robust tool that simplifies data management and enables you to derive actionable insights from data.
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