It is generally a good idea to design redundant data storage solutions. For example, it could be a fast and reliable approach to first just push everything as flat data to a static storage like s3 then have ES pull and index data from there. If you need more flexibility leveraging some ORM, you could have an RDS or Redshift layer in between. This way the data can always be rebuilt in ES.

It depends on your needs and requirements how you set the balance between redundancy and flexibility/performance. If there’s a lot of data involved, you could store the raw data statically and just index some parts of it by ES.

Amazon Lambda offers great features:

Many developers store objects in Amazon S3 while using Amazon DynamoDB
to store and index the object metadata and enable high speed search.
AWS Lambda makes it easy to keep everything in sync by running a
function to automatically update the index in Amazon DynamoDB every
time objects are added or updated from Amazon S3.