Your need to knows for MS Azure Comos DB

Dear Reader…

Today, we're pulling apart one of the more notable platforms in the Azure data landscape: Cosmos DB. We look at the upsides, downsides and latest news from Microsoft Build.

Microsoft bills Cosmos DB as a "fully managed NoSQL, relational, and vector database" for modern app development, especially for AI applications. That's a hefty claim. But for data engineers, slogging away in the trenches of modern data management, the real question is: Does it actually deliver, or is it another overhyped cloud bauble on the metaphorical Christmas tree?

For years, Data Engineers have juggled a menagerie of databases – a relational store here, a document DB there, maybe a graph database for that niche project. Cosmos DB waltzes in promising to be many things to many people, boasting APIs for NoSQL (its native tongue), MongoDB, PostgreSQL, Cassandra, and Gremlin. The allure is undeniable: One service to potentially rule them all, or at least, a significant chunk of them. But as seasoned pros, we know that flexibility often comes with its own set of headaches.

The Upside: Where Cosmos DB Shines

Let's be fair, there's a lot to like here, particularly if you're already swimming in the Azure ecosystem.

• Scalability and Performance – The Global Powerhouse: This is where Cosmos DB flexes its muscles. It's designed for "guaranteed speed at any scale," offering single-digit millisecond response times, automatic and instant scalability, and fast global access. The ability to elastically scale throughput and storage across any Azure region, even during unpredictable traffic bursts, is a massive boon for applications with global ambitions or spiky workloads. For typical 1KB items, Microsoft guarantees reads under 10ms and indexed writes under 15ms at the 99th percentile within the same region. That's pretty snappy. Plus, the recent general availability of "serverless to provisioned throughput migration" with one click and no downtime is a practical win, smoothing the path from experimental projects to production scale.

• Developer Productivity – Built for Speed (of Development): Microsoft has clearly invested in making developers' lives easier. You get SDKs for .NET, Java, Node.js, and Python, alongside drivers for the various APIs. The schema-less nature (for its NoSQL API) means you can iterate quickly, adding or modifying data properties without wrestling with DDL. The Change Feed feature is particularly handy for building event-driven architectures, allowing you to track changes to containers and trigger Azure Functions, for instance. The new JavaScript SDK v4.0, now generally available, brings an improved query pipeline, smarter bulk operations, and native support for advanced search features, which is a welcome upgrade for Node.js shops.

• AI and Vector Search – Riding the GenAI Wave: With AI being the talk of every tech town, Cosmos DB is positioning itself as a go-to database for these workloads. It now offers native vector indexing and search directly within documents, supporting multi-modal, high-dimensional vectors. This co-location of data and vectors simplifies architectures and boosts efficiency. Features like DiskANN for vector indexing, and the ability to combine vector search with standard NoSQL query filters, make it a versatile choice for building sophisticated AI applications. Indeed, Microsoft made this a cornerstone of their announcements at Build 2025.

• Mission-Critical Ready – SLAs You Can (Mostly) Bank On: Cosmos DB comes with a suite of Service Level Agreements covering throughput, latency, availability, and consistency. It offers 99.999% read availability on multi-region accounts and robust options for multi-region writes and automatic data replication. For those managing critical applications, these guarantees (and the support if things go sideways) offer a degree of peace of mind.

• The "Managed" Dream: For many of us, the idea of offloading database administration – patching, updates, scaling infrastructure – is highly appealing. Cosmos DB promises to free you from this "operational heavy lifting," letting you focus on innovation. This is a significant value proposition, especially for teams stretched thin.

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The Potential Pitfalls: Where It Might Stumble

No product is perfect, and Cosmos DB has its share of complexities and "gotchas" that experienced engineers need to watch out for.

• The Cost Factor – Handle with Care: This is probably the most cited concern. While incredibly powerful, Cosmos DB can get eye-wateringly expensive if you're not careful. The pricing model, based on Request Units per second (RU/s) and storage, requires diligent optimisation. By default, Cosmos DB indexes every field in a document, which can rack up RUs quickly. Understanding how to optimise queries, choose the right consistency level, and effectively use partitioning is crucial for cost management. As one user bluntly put it, for increasing performance, "cost is also increasing like skyrocket".

• Complexity and the Learning Curve: The sheer breadth of features and configuration options (APIs, consistency levels, indexing strategies, partitioning) means there's a significant learning curve. It's "very easy to 'shoot yourself in the foot'," as one Redditor wisely noted. Making the right choices upfront, especially around your data model and partition key, is critical.

• Partition Key Pains: Speaking of partition keys, this is a fundamental concept in Cosmos DB that you must get right. It's vital for distributing data and workload evenly. Crucially, once you set a partition key for a container, you can't change it in place. A poorly chosen partition key can lead to "hot partitions," performance bottlenecks, and costly cross-partition queries. The recent public preview of Global Secondary Indexes (GSIs) offers some relief here, allowing alternate partition keys on separate, auto-synced containers, which can help optimise query patterns without extensive data remodelling.

• Querying Quirks and Not-Quite-SQL: While the SQL API offers a familiar syntax, it's not a relational database with all the bells and whistles you might be used to from traditional SQL Server. Complex joins aren't its forte. Cross-partition queries, if your partition key isn't in the filter, can be inefficient and expensive. Some users have also found integrating with LINQ less natural than in the SQL world. Pagination, due to its cursor-based nature, has also been described as "annoying" for front-end development.

• Tooling Limitations: While the Azure portal provides management capabilities, some users find the browser-based query editor less convenient than a dedicated IDE for more complex data manipulation tasks. However, the local emulator is a definite plus for development.

Cosmos DB in Action: Real-World Scenarios

Despite the caveats, Cosmos DB is undeniably powering some serious applications across various industries:

• IoT and Telematics: Its ability to ingest bursts of data from sensors and support real-time analytics makes it a natural fit here.

• Retail and E-commerce: Used for storing product catalogues, managing inventory, and event sourcing for order processing pipelines. Companies like Jet.com (part of Walmart) have used it for elastic scalability during peak shopping periods.

• Gaming: Low latency and the ability to handle massive, unpredictable spikes in request rates are key for gaming applications.

• Social Applications & User-Generated Content: Its schema-agnostic nature is well-suited for storing diverse UGC like chat sessions, posts, and comments, where data structures can evolve rapidly.

• AI-Driven Applications: This is a major growth area, with vector search and integration with Azure AI services making it a strong contender for building the next generation of intelligent apps. HEINEKEN, for instance, uses Cosmos DB in their app architectures.

• Some other big names like: Rolls-Royce, Coca-Cola, and Siemens Healthineers are also leveraging Cosmos DB for demanding, global-scale applications, based on our research.

Hot off the Press: Microsoft Build 2025 Highlights

Microsoft is clearly doubling down on Cosmos DB, especially for AI. At Build 2025, key announcements included:

• Native Vector Search Enhancements: Further solidifying its position in the AI space.

• Global Secondary Indexes (GSIs) in Public Preview: A significant feature for improving query flexibility and performance without re-architecting data.

• JavaScript SDK v4.0 Generally Available: Modernising the developer experience for Node.js.

• Seamless Serverless to Provisioned Throughput Migration: A practical improvement for scaling workloads.

These updates underscore Microsoft's commitment to evolving Cosmos DB as a core part of its data and AI strategy.

The Final Word: Is Cosmos DB the Data Engineer's Dream or just a useful Tool?

So, after all that, should Cosmos DB be your go-to? The answer, as always in engineering, is: it depends.

If you're building globally distributed applications requiring low latency and high availability, dealing with massive scale, or diving deep into AI-driven features with vector search, Cosmos DB is a compelling, powerful option, especially if you're committed to the Azure cloud. Its multi-API support offers a degree of future-proofing and flexibility that's hard to ignore. The managed service aspect genuinely reduces operational burdens, allowing your team to focus more on building value.

However, it's not a silver bullet. The potential for high costs means you need a team that understands its intricacies and can optimise for RU/s consumption meticulously. The learning curve is real, and poor design choices, particularly around partitioning, can be painful to undo.

For the experienced Data Professional, Cosmos DB presents a powerful toolkit. It demands respect and careful planning but offers capabilities that can solve some of the toughest challenges in modern data management. It’s less of a simple Swiss Army knife and more like a sophisticated multi-tool – incredibly versatile in the right hands, but you need to know which attachment to use, and when, to avoid doing more harm than good. If you're prepared to invest the time to understand its nuances and manage its costs proactively, Azure Cosmos DB could indeed be a game-changing addition to your data arsenal.

That’s a wrap for this week

Happy Engineering Data Pro’s