Azure Cognitive Search is the correct choice for building a knowledge mining workflow across millions of unstructured records such as scanned reports and photos.

Azure Cognitive Search provides a managed search index with built in AI enrichment that can perform OCR on images, extract text and entities, and apply custom skillsets for entity recognition and language processing. This service scales to handle large ingestion volumes and integrates with other Azure services to create a complete knowledge mining pipeline that indexes and surfaces insights from diverse unstructured sources.

Google Cloud Natural Language API is a text analysis API that can extract entities and sentiment from text but it is not a managed, end to end knowledge mining index with built in document enrichment and search capabilities and it is not an Azure native solution for an archive team.

Azure Databricks is a strong platform for large scale data processing and machine learning and it can be used as part of a custom solution, but it does not provide the out of the box document enrichment pipeline and searchable index that Azure Cognitive Search offers for knowledge mining of documents and images.

Azure Form Recognizer specializes in extracting structured fields and tables from forms, receipts, and invoices and it works well for form like documents, but it is not designed to provide a full scale knowledge mining index across millions of varied unstructured records and photos without additional search and indexing infrastructure.

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