Find out in this report how the two Open Source Databases solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
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.
Once we open a support case, we have people engaged within about 20 minutes, especially for a Sev 1 issue.
The documentation and training we've received through Microsoft Learn on how to migrate, deploy, and manage the solution is exceptional.
We handle most implementations in-house, without extensive reliance on Microsoft's technical support.
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.
We can scale up compute and scale it down, but once storage is allocated, there is no way to scale it back down.
MongoDB is highly scalable.
There is a stability issue where, if the database usage peaks quickly, it may crash and require intervention to restore functionality.
We have generative AI applications, and we have not noticed any latency.
Overall, I have not encountered any real latency issues or stability concerns.
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've reduced costs by 60 percent compared to maintaining on-premises solutions.
The pay-as-you-go pricing model positively affects database-related costs by allowing us to start small and scale as needed.
The pay-as-you-go model works well for us.
We use the free version of MongoDB, so there are no licensing costs.
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.
The most valuable features of Azure Database for PostgreSQL are its networking capabilities, which allow for integration with other Azure services.
It offers flexibility in schema adaptation, allowing us to change the schema and add new data points.
Azure Database for PostgreSQL is a robust cloud solution designed to host scalable applications, manage large datasets, enable advanced analytics, and ensure data integrity through strong security features and automated backups.
Many utilize Azure Database for PostgreSQL due to its seamless integration with other Azure services and ease of setup. It supports advanced analytics and data warehousing with powerful querying capabilities. Users appreciate its high availability, automated backups, and strong security measures like advanced threat protection and encryption. Azure Database for PostgreSQL's compatibility with standard PostgreSQL ensures a smooth migration process and minimal disruption to existing applications. However, some areas needing improvement include scalability, performance under heavy loads, monitoring tools, integration with other services, documentation, support response times, and stability during peak times. Pricing is also considered high by smaller businesses.
What are the most important features of Azure Database for PostgreSQL?
What benefits and ROI should users look for?
In healthcare, Azure Database for PostgreSQL is often implemented to manage and analyze large patient datasets while ensuring data security and compliance with regulations. E-commerce companies utilize it to handle scalable transactions and customer data management, leveraging its integration with data analytics tools. Financial institutions employ it to securely store and process large volumes of financial data, relying on its robust security and automated backups.
MongoDB is a flexible and scalable NoSQL database solution that efficiently handles both structured and unstructured data. It is known for its ease of use, JSON capabilities, and efficient data handling, making it ideal for developer-friendly environments.
MongoDB stands out with features like sharding, geospatial indexing, and its open-source nature. Users find it fast and appreciate its seamless integration into different applications. Despite being powerful, it remains straightforward to set up and use, bolstered by a clustering and aggregation framework that enhances its functionality. While generally appreciated for its cost-effectiveness and broad application compatibility, there is room for improvement in security, enterprise integration, and the creation of more robust training and documentation resources. Enhancing performance and adding support for traditional relational database concepts could also prove beneficial.
What are MongoDB's most important features?MongoDB finds widespread application across industries like healthcare, logistics, and telecommunications. It efficiently powers IoT platforms, data analytics, and document management systems. Its schema flexibility and JSON storage capabilities make it ideal for real-time processing and multi-server databases, essential for handling large-scale data volumes in modern applications.
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