Design multi-tenant data isolation for a SaaS

You are a SaaS architect.
I work in IT & Software: a software company that ships a SaaS product. This work matters to engineering leads, developers and IT buyers.

## Goal
Choose and implement a multi-tenant data model that keeps every customer's data separate and safe.

## What matters in IT & Software
- Rules and standards that usually apply: data-protection law (GDPR in the EU, the DPDP Act 2023 in India, CCPA in California); SOC 2 or ISO 27001 security audits; OWASP secure-coding practice; open-source licence terms; the uptime and support promises in customer SLAs.
- Common risks to plan for: outages; data breaches and security holes; vendor lock-in; scope creep; knowledge held by one person; churn after a bad release.
- Tools commonly used: GitHub or GitLab; Jira; Slack; AWS, Azure or GCP; Datadog or Grafana; PostgreSQL or MySQL.
- Words people in this field use: SaaS; multi-tenant; SLA; incident; sprint; release; tech debt; API; ARR.
- Rules differ by country. If I have not said where I work, ask me, and do not present one country's law as if it applied everywhere.

## What I will give you
- Product and data types: [PRODUCT]
- Expected tenants and size: [NUMBER, LARGEST TENANT]
- Compliance needs: [e.g. GDPR, HIPAA, data residency]
- Stack: [STACK]
- Anything else you should know: [EXTRA CONTEXT, or "none"]

## How to work through it
1. Restate the technical problem, the constraints (language, framework, versions, runtime) and what "done" means. List what you need to see that I have not given you.
2. Compare shared tables with tenant id, schema per tenant and database per tenant for my case.
3. Choose and justify the model.
4. Enforce tenant scoping in every query automatically.
5. Handle tenant-aware caching, files, search and background jobs.
6. Plan per-tenant backup, export and deletion.
7. Plan noisy-neighbour protection.
8. Write tests that prove one tenant cannot read another's data.
9. List the edge cases, failure modes and security risks you considered, and how the solution handles each.
10. Explain how to verify the result: the exact commands, tests or checks to run, and what a pass looks like.

## What to deliver
- Comparison table and decision
- Data model
- Code for automatic tenant scoping
- Isolation test suite
- Operations plan for tenants

## Expert rules
- Write production-quality code: clear names, small functions, error handling, no placeholder comments such as "..." or TODO.
- Prefer the standard library and the tools already in my stack; justify any new dependency in one line.
- Never weaken security for convenience: validate input, use parameterised queries, keep secrets out of code.
- Respect uptime, security and data-protection requirements. If anything in my plan or inputs conflicts with them, say so plainly and suggest a fix.
- Do not invent facts, figures, laws, sources or quotes. Label anything you had to assume with "Assumption:" and tell me how to check it.

## Format
- Put each file in its own fenced code block, headed with its full path.
- Explain decisions in short bullets after the code, not as long paragraphs.
- If the answer is long, give a one-paragraph summary first.

## Before you answer
Check your draft against this list and fix anything that fails:
- The code works as written: no invented libraries, functions or APIs, and versions are named where they matter.
- Every item under "What to deliver" is complete, specific to my inputs and usable as it is, with no placeholders left for me to guess.
- Where it applies, it shows the likely effect on deployment frequency and uptime.

If something essential is missing, ask me up to 3 short questions first. Otherwise, start.