Azure SQL and Cosmos DB

What you will be able to do

• Explain the five core cloud decisions involved in azure sql and cosmos db.
• Choose a cloud resource or configuration that matches a stated workload requirement.
• Interpret provider state, workload behavior, and operational evidence before changing broader cloud state.
• Apply an inventory, select, configure, verify, recover, and document workflow to a realistic cloud decision.

01

Build the Cloud Decision Map

Compare Azure SQL and Azure Cosmos DB through data model, access patterns, consistency, scaling, managed operations, and recovery.

Cloud services combine provider-managed layers with customer-controlled configuration. A useful design keeps workload need, resource scope, identity, network path, data, health, cost, and recovery visible instead of relying on a product name.

Start with an inventory and read-only evidence. Record the account or project, location, resource identifier, owner, configuration source, dependencies, expected behavior, and current observation before changing state.

02

Azure SQL data

Azure SQL services provide managed relational database options based on the SQL Server engine family. It answers one distinct architecture or operating question within azure sql and cosmos db.

Choose an option from relational requirements, compatibility, control, availability, and migration needs. Keep the target, location, identity, configuration, and observed outcome together so another person can reproduce the reasoning.

Respect this boundary: Do not assume all Azure SQL deployment options expose identical management boundaries. The expected evidence is representative transactions and queries meet correctness and latency needs.

03

Cosmos DB items

Azure Cosmos DB is a managed distributed database that exposes supported data and API models. It answers one distinct architecture or operating question within azure sql and cosmos db.

Design partitioning and request patterns before choosing API and capacity settings. Keep the target, location, identity, configuration, and observed outcome together so another person can reproduce the reasoning.

Respect this boundary: Do not hide a poor partition key behind additional throughput. The expected evidence is required requests distribute predictably without a hot partition.

04

Managed database

Azure manages selected infrastructure, patching, availability, and backup tasks while customers own data design and access. It answers one distinct architecture or operating question within azure sql and cosmos db.

Map provider and customer operations for the exact database offering. Keep the target, location, identity, configuration, and observed outcome together so another person can reproduce the reasoning.

Respect this boundary: Do not assume managed operation removes schema, query, identity, or recovery work. The expected evidence is the responsibility map matches the selected service tier.

05

Consistency and scale

Database consistency, distribution, replicas, capacity, and indexing shape correctness, latency, availability, and cost. It answers one distinct architecture or operating question within azure sql and cosmos db.

Test representative read and write patterns under expected concurrency. Keep the target, location, identity, configuration, and observed outcome together so another person can reproduce the reasoning.

Respect this boundary: Do not weaken consistency without a business rule that tolerates it. The expected evidence is the chosen settings meet both correctness and latency targets.

06

Database recovery

Azure database recovery uses service-specific retention, restore points, replication, export, and validation capabilities. It answers one distinct architecture or operating question within azure sql and cosmos db.

Perform an isolated restore and validate application-level integrity. Keep the target, location, identity, configuration, and observed outcome together so another person can reproduce the reasoning.

Respect this boundary: Stop when restore location, encryption access, or recovery timing remains unclear. The expected evidence is the restored database meets the stated recovery objective.

07

Verify One Cloud Change

Before changing cloud state, name the exact resource, required authorization, user impact, expected signal, cost effect, and recovery path. Preview the scope with an inventory or policy view and protect data or configuration that cannot be recreated safely.

Make one narrow change and stop. If the provider response, location, identity, dependency, or effective configuration differs from the plan, preserve that evidence and reassess instead of adding unrelated changes.

A successful API response or portal notification proves only that an operation was accepted. Repeat the original workload path, inspect health and security signals, verify the resulting resource state independently, and remove temporary access or test resources.

08

Recap Before Practice and Prove

Start with azure sql data. Choose an option from relational requirements, compatibility, control, availability, and migration needs. Confirm that representative transactions and queries meet correctness and latency needs.

Keep cosmos db items separate. Design partitioning and request patterns before choosing API and capacity settings. Respect this boundary: do not hide a poor partition key behind additional throughput.

Use managed database as its own decision. Map provider and customer operations for the exact database offering. Preserve the resulting evidence.

Before a broader change, review consistency and scale. Test representative read and write patterns under expected concurrency. Stop when do not weaken consistency without a business rule that tolerates it.

Finish with database recovery. Perform an isolated restore and validate application-level integrity. Record the final state, health signal, recovery boundary, owner, and next decision.