# Data Lake A data lake is a centralized storage repository that holds large volumes of raw data in its native format until it is needed for analysis. Unlike a data warehouse, which stores data in a structured, processed format, a data lake retains data in its original form -- structured, semi-structured, or unstructured. Data lakes are built on scalable storage systems such as AWS S3, Azure Data Lake Storage, or Google Cloud Storage. They support diverse data types including log files, JSON documents, images, and streaming data. Processing frameworks like Apache Spark and Presto query data in place without requiring it to be loaded into a separate database. In API-driven systems, data lakes often serve as the destination for API analytics and logging data. API gateway access logs, request metadata, and performance metrics can be streamed into a data lake for later analysis. This enables teams to identify usage patterns, detect anomalies, and make data-driven decisions about API design and capacity planning. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.serverlessapigateway.com/glossary/d/data-lake.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.