Cost-Effective Storage for Cold Analytics Data on Azure
A company is designing a solution to store and analyze petabytes of IoT sensor data. The data is written once, rarely accessed, and must be retained for 10 years for compliance. The data must be queryable using SQL. Which combination of Azure services would be MOST cost-effective?
Quick Answer
The answer is Azure Data Lake Storage Gen2 with Azure Synapse Serverless SQL. This combination is the most cost-effective for cold analytics data because ADLS Gen2 offers low-cost, scalable storage optimized for petabyte-scale data that is written once and rarely accessed, while Azure Synapse Serverless SQL enables on-demand SQL querying directly over the stored files without provisioning dedicated compute resources, eliminating idle costs. On the AZ-305 exam, this scenario tests your ability to match storage and compute services to data lifecycle patterns, specifically for cold data requiring long-term retention and occasional SQL-based analysis. A common trap is choosing Azure SQL Database or Cosmos DB, which are designed for transactional or warm data and become prohibitively expensive at petabyte scale. Remember the key principle: for cold analytics, separate cheap storage from serverless compute. Memory tip: “Cold data needs cold storage and hot-on-demand querying” — think ADLS for the icebox and Synapse Serverless for the occasional thaw.
⚠ Common exam trap
Watch out — candidates often choose Azure SQL Database or Cosmos DB because they associate SQL queryability with traditional databases, overlooking that serverless SQL engines over cheap blob storage can provide the same query capability at a fraction of the cost for cold data.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure Data Lake Storage Gen2 with Azure Synapse Serverless SQL
Azure Data Lake Storage Gen2 (ADLS Gen2) provides cost-effective, scalable storage for petabytes of data at low cost, while Azure Synapse Serverless SQL enables on-demand SQL querying directly over the data in ADLS Gen2 without provisioning dedicated compute. This combination meets the write-once, rare-access, 10-year retention, and SQL queryability requirements at the lowest cost because storage is cheap and compute is only billed per query executed.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure Cosmos DB with analytical store
Why it's wrong here
High cost for petabytes.
- ✗
Azure SQL Database with Hyperscale tier
Why it's wrong here
Expensive for cold data.
- ✓
Azure Data Lake Storage Gen2 with Azure Synapse Serverless SQL
Why this is correct
Cost-effective storage and SQL querying.
- ✗
Azure Databricks with Delta Lake
Why it's wrong here
More expensive for simple queries.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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About these practice questions
One of 212 original AZ-305 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
1 more way this is tested on AZ-305
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. You are designing a storage strategy for a data analytics solution that processes large volumes of streaming data. The data must be stored in a cost-effective manner with low latency for hot data and infrequent access for cold data after 30 days. The solution must support both batch and interactive queries. Which combination of Azure storage services should you recommend?
hard- ✓ A.Azure Data Lake Storage Gen2 with lifecycle management
- B.Azure SQL Database with geo-replication
- C.Azure Blob Storage with hot and cool access tiers
- D.Azure Cosmos DB with multiple consistency levels
Why A: Azure Data Lake Storage Gen2 (ADLS Gen2) combines the scalability and cost benefits of object storage with a hierarchical namespace, enabling both batch and interactive queries via services like Azure Synapse Analytics and Apache Spark. Lifecycle management policies can automatically transition hot data to cooler tiers (e.g., cool or archive) after 30 days, reducing costs for infrequently accessed cold data while maintaining low-latency access for hot data. This makes ADLS Gen2 the ideal choice for streaming data analytics that requires cost-effective tiered storage and supports diverse query patterns.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AZ-305 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AZ-305 exam.