

Microsoft Azure Cosmos DB and Azure Database for PostgreSQL are competing in the database services category. Azure Cosmos DB appears to have the upper hand for dynamic applications thanks to its scalability and flexibility, while Azure Database for PostgreSQL provides a robust, cost-effective solution for structured data environments.
Features: Azure Cosmos DB offers scalability, API support for seamless integration, and efficient management of high-volume data. Azure Database for PostgreSQL provides SQL compatibility, robust features for structured data processing, and reliable query performance and feature sets.
Room for Improvement: Azure Cosmos DB needs to improve its documentation, interface for complex queries, and pricing transparency. Azure Database for PostgreSQL could enhance its scalability, performance stability during peak loads, and analytics features.
Ease of Deployment and Customer Service: Azure Cosmos DB is mostly deployed on the public cloud and is praised for its setup and integration but criticized for its cost structure. Customer service is mixed in quality. Azure Database for PostgreSQL allows deployment across public, private, and hybrid clouds, providing flexibility. Its customer service is generally responsive, although additional SQL training for staff could improve user experience.
Pricing and ROI: Azure Cosmos DB's pricing is perceived as complex and high, reliant on a resource unit model that requires careful optimization for ROI. Its scalable features can result in cost savings with efficient planning. Azure Database for PostgreSQL, with straightforward pay-as-you-go pricing, is seen as more affordable, enhancing cost management and scalability.
It offers at least 25 percent cost savings compared to maintaining on-premises databases.
Now, we use embedded PostgreSQL vectors, which will undoubtedly reduce the TCO by using a much more cost-effective solution.
We've reduced our total ownership cost because we are not spending on expensive SQL server licenses.
Getting an MVP of that project would have taken six to eight months, but because we had an active choice of using Azure Cosmos DB and other related cloud-native services of Azure, we were able to get to an MVP stage in a matter of weeks, which is six weeks.
You can react quickly and trim down the specs, memory, RAM, storage size, etc. It can save about 20% of the costs.
When I have done comparisons or cost calculations, I have sometimes personally seen as much as 25% to 30% savings.
Once we open a support case, we have people engaged within about 20 minutes, especially for a Sev 1 issue.
On a scale from one to ten, I rate customer service and technical support a nine because they are quick in responding and in working with me to rectify any issues we come across.
The documentation and training we've received through Microsoft Learn on how to migrate, deploy, and manage the solution is exceptional.
Premier Support has deteriorated compared to what it used to be, especially for small to medium-sized customers like ours.
The response was quick.
I would rate customer service and support a nine out of ten.
We do not have to buy everything and build it. It is already there.
However, we can see how well it scales after we deploy it for some large enterprise customers or big government organizations.
The scaling options with FlexServer provide us with the flexibility we need based on application complexity.
The system scales up capacity when needed and scales down when not in use, preventing unnecessary expenses.
We like that it can auto-scale to demand, ensuring we only pay for what we use.
We have had no issues with its ability to search through large amounts of data.
It is the go-to database if seeking performance and capacity.
I have not experienced any downtime, crashes, or performance issues; it has been very stable.
There is a stability issue where, if the database usage peaks quickly, it may crash and require intervention to restore functionality.
We have multiple availability zones, so nothing goes down.
Azure Cosmos DB would be a good choice if you have to deploy your application in a limited time frame and you want to auto-scale the database across different applications.
I would rate it a ten out of ten in terms of availability and latency.
It does not presently support knowledge graph functionalities as Neo4j does.
Azure Database for PostgreSQL can be improved by allowing quicker scaling without blips.
I believe there could be improvements in the mirroring part and Change Data Capture (CDC).
We must ensure data security remains the top priority.
You have to monitor the Request Units.
The dashboard could include more detailed RU descriptions, IOPS, and compute metrics.
We've reduced costs by 60 percent compared to maintaining on-premises solutions.
We chose it because it is more cost-effective than Microsoft SQL.
Once you are comfortable and ready to make some commitments, you get about 30 percent saving if you are going with one-year or three-year reservation cost.
Initially, it seemed like an expensive way to manage a NoSQL data store, but so many improvements that have been made to the platform have made it cost-effective.
Cosmos DB is expensive, and the RU-based pricing model is confusing.
Cosmos DB is great compared to other databases because we can reduce the cost while doing the same things.
My takeaway as a CTO is that they're comfortable with the security posture, the features, the observability, alerts, and now it integrates into the rest of the Azure landscape.
The query analyzers help me find out what's happening in each of the queries.
If a database has any task that has been interrupted or any connection issue, it will alert LogicMonitor, and we have a centralized panel for all the alerts.
The most valuable feature of Microsoft Azure Cosmos DB is its real-time analytics capabilities, which allow for turnaround times in milliseconds.
Performance and security are valuable features, particularly when using Cosmos DB for MongoDB emulation and NoSQL.
The performance and scaling capabilities of Cosmos DB are excellent, allowing it to handle large workloads compared to other services such as Azure AI Search.
| Product | Market Share (%) |
|---|---|
| Microsoft Azure Cosmos DB | 4.1% |
| Azure Database for PostgreSQL | 3.3% |
| Other | 92.6% |

| Company Size | Count |
|---|---|
| Small Business | 3 |
| Midsize Enterprise | 4 |
| Large Enterprise | 16 |
| Company Size | Count |
|---|---|
| Small Business | 33 |
| Midsize Enterprise | 21 |
| Large Enterprise | 58 |
Azure Database for PostgreSQL offers efficient management, robust networking, and seamless Microsoft integration. Known for its strong performance and high satisfaction in enterprise settings, it provides operational efficiency, security, and monitoring.
With features that facilitate Azure integration, easy configuration, and AI integration, Azure Database for PostgreSQL serves as a valuable choice for businesses requiring operational efficiency and cost-effectiveness. Users benefit from powerful vector capabilities, seamless Microsoft service integration, straightforward management, and user authentication ensuring high satisfaction. Easy optimization, query analysis, and backup operations make it suitable for varied enterprise applications. However, improvements in flexible scaling, cost-effectiveness of monitoring tools, and enhanced integration with Azure OpenAI would enhance its capabilities further.
What Are the Key Features of Azure Database for PostgreSQL?Industries such as healthcare, retail, and finance leverage Azure Database for PostgreSQL for backend solutions, incident reporting, and public information sharing. Managed service providers utilize its strong performance for client needs, while administrators use it for applications like ControlM. Its flexibility supports containerized applications and disaster recovery, ensuring compatibility with diverse environments.
Microsoft Azure Cosmos DB offers scalable, geo-replicated, multi-model support with high performance and low latency. It provides seamless Microsoft service integration, benefiting those needing flexible NoSQL, real-time analytics, and automatic scaling for diverse data types and quick global access.
Azure Cosmos DB is designed to store, manage, and query large volumes of both unstructured and structured data. Its NoSQL capabilities and global distribution are leveraged by organizations to support activities like IoT data management, business intelligence, and backend databases for web and mobile applications. While its robust security measures and availability are strengths, there are areas for improvement such as query complexity, integration with services like Databricks and MongoDB, documentation clarity, and performance issues. Enhancements in real-time analytics, API compatibility, cross-container joins, and indexing capabilities are sought after. Cost management, optimization tools, and better support for local development also require attention, as do improvements in user interface and advanced AI integration.
What are the key features of Azure Cosmos DB?Industries use Azure Cosmos DB to support business intelligence and IoT data management, using its capabilities for backend databases in web and mobile applications. The platform's scalability and real-time analytics benefit sectors like finance, healthcare, and retail, where managing diverse datasets efficiently is critical.
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