A database specialist is designing the database for a software-as-a-service (SaaS) version of an employee information application. In the current architecture, the change history of employee records is stored in a single table in an Amazon RDS for Oracle database. Triggers on the employee table populate the history table with historical records. This architecture has two major challenges. First, there is no way to guarantee that the records have not been changed in the history table. Second, queries on the history table are slow because of the large size of the table and the need to run the queries against a large subset of data in the table. The database specialist must design a solution that prevents modification of the historical records. The solution also must maximize the speed of the queries. Which solution will meet these requirements?

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B. Write employee record history to Amazon Quantum Ledger Database (Amazon QLDB) for Amazon Quantum Ledger Database (QLDB) is purpose-built for immutable and cryptographically verifiable transaction logs, ensuring that historical employee records cannot be altered. Its ledger-like structure and indexing capabilities are optimized for querying historical data, directly addressing both the data integrity and query performance requirements for a large history table.

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A. Migrate the current solution to an Amazon DynamoDB table. Use DynamoDB Streams to keep While Amazon DynamoDB is scalable, it does not inherently provide cryptographic verifiability for data immutability, and DynamoDB Streams are for capturing changes, not for guaranteeing the integrity of historical records in the table itself.

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C. Use Amazon Aurora PostgreSQL to store employee record history in a single table. Use Aurora Amazon Aurora PostgreSQL is a relational database that, like Oracle RDS, does not natively provide cryptographic immutability guarantees for historical data, nor does it inherently solve performance challenges for very large history tables without significant indexing and partitioning efforts.

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D. Build a solution that uses an Amazon Redshift cluster for historical records. Query the Redshift Amazon Redshift is a data warehouse optimized for analytical queries on large datasets, which could improve query performance, but it does not offer the cryptographic immutability and data verifiability that QLDB provides for historical records.

A database specialist is designing the database for a software-as-a-service (SaaS) version of an employee information application. In the current architecture, the change history of employee records…

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