Azure Table Storage for Log Data
You need to store billions of small log entries (each ~200 bytes) generated from multiple IoT devices. The logs are written in chronological order and are rarely updated. You need to run queries that scan large ranges of data by timestamp each day. You want to maximize write throughput and minimize storage costs. Which Azure Storage solution should you choose?
Quick Answer
The answer is Azure Table Storage with a partition key combining device ID and date, and row key as timestamp. This design is correct because it leverages Table Storage’s schema-free, key-value architecture to maximize write throughput by distributing billions of small log entries across many partitions, while the row key as timestamp enables fast, server-side range queries over chronological data without the overhead of a separate index. On the AZ-204 exam, this scenario tests your understanding of how to balance partition distribution for high-volume writes against the need for efficient range scans—a common trap is choosing Cosmos DB for its indexing, which would increase cost and latency for this simple log workload. Remember the memory tip: “Partition by device and date, row key by time—logs scale fine.”
⚠ Common exam trap
Many candidates choose Cosmos DB for its indexing and query capabilities, overlooking the fact that Table Storage provides native, cost-effective range queries on the row key without additional indexing costs, making it the optimal choice for high-volume, low-cost log storage with timestamp-based scans.
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 Table Storage with a partition key combining device ID and date, and row key as timestamp.
Azure Table Storage is ideal for this scenario because it supports high-volume, low-cost storage of structured log data with efficient range queries. By using a partition key of device ID combined with date, you distribute writes across partitions for high throughput, while the row key as timestamp enables fast, server-side range scans over chronological data without the overhead of a separate index.
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 SQL API with a collection partitioned by timestamp.
Why it's wrong here
Cosmos DB provides low-latency access and flexible queries, but it is significantly more expensive than Azure Table Storage for high-volume log ingestion. The cost per GB is much higher, and write throughput is billed per RU.
- ✗
Azure Blob Storage with append blobs and a custom index for timestamp queries.
Why it's wrong here
Append blobs are good for sequential writes, but querying by timestamp across billions of small entries would require a separate index and is less efficient than Table Storage's built-in row key indexing.
- ✓
Azure Table Storage with a partition key combining device ID and date, and row key as timestamp.
Why this is correct
Correct. Table Storage provides high throughput at low cost. By designing the partition key appropriately, you can achieve efficient range queries on timestamps and handle billions of entries.
- ✗
Azure SQL Database with a clustered columnstore index.
Why it's wrong here
SQL Database is not designed for such high-volume unstructured log data at low cost. It would be expensive and the schema would need to be rigid, while Table Storage provides schema-less tables.
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Same concept, more angles
2 more ways this is tested on AZ-204
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 need to store billions of small log entries (each ~200 bytes) written in chronological order from multiple producers. The logs are read sequentially in bulk once per day. You need to maximize write throughput and minimize storage costs. Which Azure Storage solution should you choose?
hard- ✓ A.Append Blob in Blob Storage
- B.Block Blob in Blob Storage with high block count
- C.Azure Data Lake Storage Gen2 with hierarchical namespace
- D.Azure Files with SMB protocol
Why A: Append Blob in Blob Storage is optimized for append operations, making it ideal for writing small log entries in chronological order from multiple producers. It provides high write throughput because each append operation is atomic and can be performed concurrently, and it minimizes storage costs by storing data in a cost-effective blob tier without the overhead of indexing or metadata management required by other solutions.
Variation 2. You need to store billions of small telemetry data entries (each ~100 bytes) from IoT devices. The data is written once and rarely updated. You need to run analytical queries on the last 30 days of data daily. The queries scan large ranges of data by timestamp and require sub-second response times. You need the lowest storage cost while meeting query latency requirements. Which Azure Storage solution should you use?
hard- ✓ A.Azure Blob Storage with hot access tier and Data Lake Storage Gen2.
- B.Azure Table Storage with a timestamp partition key.
- C.Azure Cosmos DB with SQL API and automatic indexing.
- D.Azure Blob Storage with cool access tier and Azure Data Lake Storage Gen2.
Why A: Azure Blob Storage with the hot access tier is suitable for data that is accessed frequently (daily queries on the last 30 days), providing lower transaction costs compared to the cool tier for active data. Azure Data Lake Storage Gen2, built on Blob Storage, enables hierarchical namespace and POSIX-like access, allowing efficient analytical queries on large timestamp-ranged data with sub-second response times via partitioning and parallel processing, meeting the performance and scalability requirements at a cost-effective price point for the storage of billions of small entries.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AZ-204 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-204 exam.