Observed Signal · Jun 24, 2026 · Technical Article · Source: DEV Community · Impact: 2/5 · Sentiment: Neutral
When SQL Isn't Right: Cosmos DB vs Blob Storage
This technical blog post explains when relational SQL databases are the wrong fit and outlines two Azure alternatives: Azure Cosmos DB for flexible JSON documents and Azure Blob Storage for unstructured files. It describes Cosmos DB concepts (account, database, container, item), emphasizes the critical importance of choosing an appropriate partition key, and explains billing via Request Units with provisioned and serverless modes. For Blob Storage the article covers blob types (block, append, page), storage tiers (Hot, Cool, Archive), and Shared Access Signatures (SAS) for scoped temporary access. The author contrasts Azure SQL, Cosmos DB and Blob Storage and offers practical guidance for matching data shape and access patterns to the right Azure service.
Practical technical guidance on choosing Azure storage/database services is useful to engineers building cloud-backed MarTech/AdTech systems, but the article is explanatory rather than introducing platform changes or industry-wide impact.
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Key Takeaways & Evidence Grounding
- Azure Cosmos DB is a fully managed NoSQL database that stores JSON documents and supports multiple APIs (NoSQL, MongoDB, Cassandra, Gremlin, Table).
- Cosmos DB billing uses Request Units (RUs); two throughput modes exist: provisioned throughput and serverless mode.
- The partition key in Cosmos DB is critical for data distribution and performance; poor choices can create hot partitions.
- Azure Blob Storage stores unstructured files (blobs) in containers, provides Hot/Cool/Archive tiers, and supports blob types: Block, Append, and Page blobs.
- Shared Access Signatures (SAS tokens) grant temporary, scoped access to blobs or containers without exposing account keys.
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How to Change Partition Key in Azure Cosmos DB
The article explains that a container's partition key in Azure Cosmos DB is fixed at creation and cannot be changed in-place, so changing keys requires moving data to a new container. It outlines four approaches and their tradeoffs: the Azure portal "Change partition key" feature (managed, low effort), container copy jobs via CLI (scriptable, online/offline modes), a custom migration pipeline using bulk ingestion/ADF/Spark and change feed (maximum control), and a Global Secondary Index (GSI) to support different read patterns without moving writes. Key operational considerations include online vs offline copy modes, RU cost impacts, prerequisites like continuous backup and all-versions-and-deletes change feed, TTL behavior, and creation-time-only settings like hierarchical partition keys.
Database Choices That Cause Long‑Term Pain
An opinion/technical guidance post (published 2026-05-16) by Qodors on DEV explains how early database decisions commonly create technical debt within about two years. The article reviews trade-offs between common options — MongoDB, Postgres, Firebase, SQL Server/Azure SQL — and highlights recurring operational mistakes: missing indexes, lack of migration strategy, mixing workloads, ignoring read/write patterns, and untested backups. It recommends five concrete pre-selection questions (data shape, read/write ratios, growth expectations, team expertise, and exit cost) to reduce costly refactors and outages as systems scale.
Create Highly Available Azure Storage for Public Website
This technical tutorial explains how to host public files or a static website on Microsoft Azure Blob Storage with high availability and safety features. It walks through creating an Azure storage account, selecting Read‑access Geo‑redundant storage for cross‑region availability, enabling anonymous blob access so files are publicly viewable, creating a public blob container, uploading and testing files, and enabling data protection features such as blob soft delete (set to 21 days) and blob versioning. The guide is a step‑by‑step how‑to for configuring Azure storage settings via the Azure Portal.
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