

MongoDB Enterprise Advanced and Azure Database for PostgreSQL compete in the database market, each offering unique advantages. Based on features and integration, Azure Database for PostgreSQL takes the lead due to its strong integration with Azure services and robust support structure.
Features: MongoDB Enterprise Advanced is known for its flexibility, scalability, and ability to handle large amounts of unstructured data. It is developer-friendly, supports complex queries, and is valued for its open-source nature. Azure Database for PostgreSQL excels in integration with Azure services, offering solid performance and relational database functionality, with a seamless integration experience within the Microsoft ecosystem.
Room for Improvement: MongoDB Enterprise Advanced could improve its enterprise integration, particularly in audit and security features, and enhance its pricing structure and support options. Azure Database for PostgreSQL has room to grow in scaling capabilities and real-time reporting, while its security and pricing model could also see improvements.
Ease of Deployment and Customer Service: MongoDB Enterprise Advanced provides multiple deployment options suitable for on-premises and hybrid cloud, but often relies on community resources for support. Azure Database for PostgreSQL integrates well with Microsoft products and offers comprehensive technical support, appearing more favorable for enterprises using the Azure infrastructure.
Pricing and ROI: MongoDB Enterprise Advanced offers cost-effectiveness through its open-source model, though enterprise licensing can be expensive. Azure Database for PostgreSQL uses a flexible pay-as-you-go model that might lead to increased costs if not properly managed. Both offer ROI, with MongoDB providing savings for startups while Azure supports larger enterprises seeking seamless integration within Microsoft's ecosystem.
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.
Actually, with MongoDB, it's difficult to calculate the return on investment; it's too expensive for our use.
I would say we see value in money and return on investment with MongoDB Enterprise Advanced.
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.
We have received fairly good support whenever we reached out to the technical teams; they were prompt.
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.
In CosmoDB, the scalability is much better than with the MongoDB ReplicaSet models.
MongoDB is highly scalable.
Overall, on a scale of one to ten, I would rate MongoDB an eight; it's mostly because we're still running a monolithic environment on old hardware, so there are some limitations with read-write access.
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.
It's pretty much stable; we have not faced any major challenges or difficulties with MongoDB Enterprise Advanced.
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).
While solutions for other databases like SQL or PostgreSQL already exist, MongoDB requires additional integrations for developing AI solutions.
We have not contracted the security options in our contract because they're too expensive; thus, we implement just encrypted databases and not the security pack.
From the AWS standpoint, if robust integration and data warehouse integration specific tools are added in the advanced suite, that would definitely be helpful.
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.
We use the free version of MongoDB, so there are no licensing costs.
We have to pay approximately 2,000 euros per month for MongoDB.
For a small company, the cost of MongoDB Enterprise Advanced is reasonable, but for heavy data usage, we see a little bit of cost pressure but it's acceptable.
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.
It offers flexibility in schema adaptation, allowing us to change the schema and add new data points.
In ReplicaSet, it's acceptable, but if your workload needs more performance, and you must pass to a Sharding model, it becomes complicated in MongoDB; in Cosmos DB, however, it's simple.
MongoDB has definitely helped us improve our network monitoring and reporting dashboard.
| Product | Mindshare (%) |
|---|---|
| Azure Database for PostgreSQL | 1.3% |
| MongoDB Enterprise Advanced | 5.1% |
| Other | 93.6% |

| Company Size | Count |
|---|---|
| Small Business | 3 |
| Midsize Enterprise | 4 |
| Large Enterprise | 16 |
| Company Size | Count |
|---|---|
| Small Business | 35 |
| Midsize Enterprise | 13 |
| Large Enterprise | 38 |
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.
MongoDB Enterprise Advanced is a comprehensive platform renowned for its scalability, user-friendliness, and high performance, underpinned by its flexible document-based storage and open-source model. JSON compatibility, clustering, and security elevate its standing among professionals.
The platform facilitates efficient data management through developer-friendly tools and a strong aggregation framework. MongoDB’s no-schema requirement, supported by community expertise, underlines its adaptability. While its sharding capabilities and affordably support large data volumes, there are aspects such as security enhancement and enterprise tool integration that need attention. Indexing and query optimization pose challenges, alongside high costs. Improvements in analytics and UI could advance its infrastructure further.
What are the key features of MongoDB Enterprise Advanced?Industries leverage MongoDB Enterprise Advanced for significant roles in data storage within IoT platforms, healthcare apps, public service monitoring, and big data analytics. Companies in logistics and telecommunications find it instrumental for business process management and video content management, benefiting from its seamless integration and unstructured data support.
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