Read-only database: Normalize or not for best query performace
All things being equal, a normalized database will provide better performance for a wide range of queries.  It is a myth that a normalized database will be slow, especially in an analytic environment or with a large number of rows.  Usually if performance suffers, it is because a database has not been properly normalized.
A normalized database also provides for better data integrity which, depending on your industry and whether or not you are storing data related to payments, may be necessary.
However, if you're just looking to dump data, not perform any sort of transforms, always return the exact type of data, and use the same access path you probably don't need to spend as much time normalizing the data to meet your requirements.
But it would still make sense to use a relational engine that features B-Trees (and preferably clustered indexes/index organized tables) to speed data recovery.  Some NoSQL engines support methods to quickly access single records (Hash maps, occasionally B-Trees), but they won't offer the flexibility of a good RDBMS (not SQLite).
Another thing to consider is staying power/support.  Many database engines have existed in a mature form for 30+ years and have existing tools developed to assist with backups/ETL/maintenance, a knowledge base, developers experienced in their use, and some assurance the worst bugs have been worked out (MongoDb was awful in that regard early on).
From comment:

I am storing payments. Why does a normalized database provides better
data integrity?

So it depends on whether you are handling payments in real time versus storing an archive history, but generally a relational database is preferable because:

Transactions can enforce complex operations are performed in a way that keeps the database consistent.
All operations against the database are logged, so changes made between backups are auditable.
With the right primary key definition, uniqueness is guaranteed and all totals/calculations performed will be consistent.
With the right clustered index and/or partitioning scheme, aggregation is very fast.