Best Practices for Deployments with Large Data Volumes

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Best Practices for Deployments with Large Data Volumes
Introduction
Underlying Concepts
Infrastructure for Systems with Large Data Volumes
Techniques for Optimizing Performance
Best Practices
Reporting
Loading Data from the API
Extracting Data from the API
Searching
SOQL and SOSL
Deleting Data
General
Large Data Volumes Case Studies
Summary
PDF

General

Goal Best Practice
Avoiding sharing computations Avoid having any user own more than 10,000 records.
Improving performance Use a data-tiering strategy that spreads data across multiple objects, and brings in data on demand from another object or external store.
Reducing the time it takes to create full copies of production sandboxes with large data volumes When creating copies of production sandboxes, exclude field history if it isn’t required, and don’t change a lot of data until the sandbox copy is created.
Making deployments more efficient Distribute child records so that no parent has more than 10,000 child records. For example, in a deployment that has many contacts but does not use accounts, set up several dummy accounts and distribute the contacts among them.