What advice do you have for others considering Microsoft Azure Cosmos DB?

I would rate Microsoft Azure Cosmos DB eight out of ten. It took us three months to be fully onboarded with Cosmos DB. The learning curve for Cosmos DB is certainly different from SQL databases. While most developers become proficient with basic functionality within a week or two, achieving true expertise in Cosmos DB requires a considerably longer time investment due to its unique architecture and features. The maintenance is handled by Microsoft. Be very careful with your partition keys when using Cosmos DB.

I rate Cosmos DB ten out of ten. While there is a learning curve when transitioning from traditional SQL databases to NoSQL databases, this is not specific to Cosmos DB. Regardless of the provider, understanding NoSQL requires a shift in approaching data storage and retrieval, particularly for those familiar with relational databases. This inherent learning curve stems from the fundamental differences between the two database types and necessitates learning new concepts and techniques for effectively working with NoSQL databases. No maintenance is required. For newcomers, it is crucial to understand that despite the SQL API, Cosmos DB is not a traditional SQL database. Many issues arise when trying to apply relational database principles. Understanding NoSQL databases' limitations and adapting to the mindset required is essential.

To new users, I would advise first knowing their data. They should know whether it fits their solution, which Azure Cosmos API to use, and what scale they intend to run it. I would rate Microsoft Azure Cosmos DB a nine out of ten.

I would rate Microsoft Azure Cosmos DB eight out of ten. Understanding some of the subtleties of Microsoft Azure Cosmos DB can take time, and some individuals at ASOS still find concepts like partitioning unclear. However, getting started with Cosmos DB and developing functional applications is quick and can be achieved in a short timeframe. We require minimal maintenance to validate that we've configured, for example, the correct indexing policies as required by our queries. New users should make sure they understand partitioning because once it's selected, it is difficult to change it. Otherwise, you would need to migrate everything over to another collection.

I would advise taking advantage of all of the features that are available. Especially if you are a globally distributed business, make sure that you have all of the high availability and backup options enabled so that you are not surprised in case of a problem. Like almost all of the recommendations that you see in different Microsoft videos, make sure that your partition keys are set up properly from a RU perspective so that you know that you will be able to scale your individual containers effectively without running into the limitation of 20-gigabyte physical partition size or 10,000 RU physical partition throughput. Be aware that those exist and design your partition keys for the future so that you will not be limited when your system starts to get heavily utilized in the future. I would rate Azure Cosmos DB an eight out of ten. There are some improvements that I would like to see around the physical partitions.

I rate Microsoft Azure Cosmos DB ten out of ten. We use Azure Cosmos DB extensively for searching alongside Azure AI Search, which offers full-text Lucene syntax-compatible querying. While a significant portion of our searches leverage these dedicated search indexes, we still conduct a fair amount directly in Azure Cosmos DB. Although it might not be entirely fair to say that searching isn't Azure Cosmos DB's strong suit, it's worth noting that its capabilities are constrained by partitioning requirements. This limitation places a ceiling on its overall effectiveness for specific scenarios. While Azure Cosmos DB can be extremely valuable for querying within partitions, alternative solutions are often better suited for queries spanning multiple partitions. I've built tools around the Azure Cosmos DB SDKs to make them incredibly easy to use. My team had no learning curve and could leverage our shared libraries. It took me less than a week to achieve a production-quality implementation for accessing and saving data within a platform. We have 20 people in the organization who interact with Azure Cosmos DB, consisting of 15 engineers and five others. Azure Cosmos DB typically requires minimal maintenance, but if data partitioning is not done correctly, some overhead may be incurred due to the need to replicate containers and move data. Thus, while generally low maintenance, some maintenance can be required in certain situations. For anyone thinking about implementing Azure Cosmos DB, first, understand your data and invest time in understanding the partitioning in Azure Cosmos DB. If you get your head wrapped around the partitioning, everything else will be straightforward.

I would recommend using it, but with a caveat – it's a good fit for companies with deep pockets. It's powerful and amazing, but the costs can add up. I'd give it an eight out of ten. It's super powerful and solves real problems with global distribution. I hesitate to give it a perfect ten because it's still new, and good training resources are harder to find. Even the most recent books on Cosmos DB are several years old, which is ancient in IT terms. I had to work hard to get a certification in it.

If the cost is affordable and you're looking for a managed service for unstructured data, I would definitely recommend using Cosmos DB from Azure. It also has seamless migration options from MongoDB, MySQL, and others. So, a managed service is the best way to go if the cost is affordable. Overall, I would rate the solution a seven out of ten.

For those considering Cosmos DB, my advice is to embrace its versatility. Cosmos DB can handle various data models like documents, wide columns, and graphs seamlessly. You can consolidate your needs into one database, Cosmos, eliminating the need for multiple databases. It simplifies management and offers a comprehensive solution for a wide range of use cases. Overall, I would rate Microsoft Azure Cosmos DB as an eight out of ten.

Cosmos DB is a good option if someone is looking for a NoSQL database. Overall, I rate the product a nine out of ten.

Microsoft Azure Cosmos DB is deployed on-cloud in our organization. I would recommend Microsoft Azure Cosmos DB to other users. Overall, I rate Microsoft Azure Cosmos DB a seven out of ten.

I rate Microsoft Azure Cosmos DB an eight out of ten. It is useful to store original data in original format.

If a customer needs to store JSON data, and the solution doesn't require complex structure and reporting like BI reports and RDBMS, opting for a NoSQL database could be ideal. NoSQL databases are suitable when data isn't structured in a relational manner and when extensive normalization isn't a priority. For efficiently handling JSON data for UI purposes or other needs, a NoSQL database like Cosmos DB is the way to go. However, in the NoSQL landscape, various options like Redis DB, CouchDB, MongoDB, and Cosmos DB exist. If a preference leans towards Microsoft technologies, then Cosmos DB becomes a logical choice. Comparing Cosmos DB with alternatives like Redis DB is advisable before making a final decision. Thus, my typical recommendation involves considering these factors. I would Cosmos DB a nine out of ten.

I would overall rate the solution an eight out of ten.

I would recommend understanding the underlying databases like Cosmos DB, but I don't think it supports Oracle. However, it does support various other databases. If it supports the databases you need, then go for it. If it doesn't support them, there's not much you can do. Overall, I would rate the solution an eight out of ten. I'm not giving it a higher rating because it doesn't support all databases.

It's a highly scalable, highly robust, and very user-friendly solution. It is easy to set up; the most important point is that it is on a cloud. The solution is also very easy to deploy. Only some connectivity features need to be developed. I give it an eight out of ten.

If your existing infrastructure already uses Microsoft services or is more of a Microsoft-dependent solution, it's best to be on Microsoft Azure cloud. This is because it integrates very well, and there is a smooth integration with other Microsoft products that are already running on our products. You can also leverage some of your existing licenses, saving you a lot of costs when you move to the cloud. That's one solution I would suggest for anyone who is moving from on-premise to the cloud. Overall, I would rate the solution an eight out of ten.

I would rate this solution as 8 out of 10. When it comes to ease of use, spinning up and working at scale, our specific use case, and the scalability that it offers, the solution is definitely very good. My advice is to use containers as single objects and create manual indexing to improve efficiency.

I would rate this solution as eight out of ten. The APIs are improving and are easy to use. It is easy to set up a new database, and the auto scalability and support for different models are good features.

I rate the solution a nine out of ten.

I would recommend this solution to others who are interested in using it. I would rate Microsoft Azure Cosmos DB a seven out of ten.

My general advice to anyone looking to implement Microsoft Azure would be to start small. When you see your application increase or your traffic increase on site, you can slowly scale. I would rate the solution a seven out of 10 overall.

The cost is the biggest limitation of this solution. I would rate this solution a six out of ten.

I've been using Microsoft Azure Cosmos DB, a cloud DB solution. It's deployed in a cloud environment, on a public cloud with security for ourselves. My company is a partner of Microsoft and also a reseller. My advice to people looking into implementing Microsoft Azure Cosmos DB is that it would be good for them to use, specifically if they are looking for a NoSQL database to ingest the data and do data discovery using the data in a BI tool. It's easy to ingest the data and work with the data in Microsoft Azure Cosmos DB and understand that, because it is not a SQL database, which means it's not as structured. You can add data, and then do a data discovery, and use it the best way for you. I would recommend Microsoft Azure Cosmos DB. My rating for Microsoft Azure Cosmos DB is eight out of ten.

I would recommend this solution to others. I rate Microsoft Azure Cosmos DB a nine out of ten.

I rate Cosmos DB eight out of 10. I would recommend it for an appropriate use case. However, you need to be aware of the system's limitations. If you're using the DocumentDB system, it's crucial to plan properly for document structure, etc. You also need to plan for failure to ensure that your system can survive when any node fails. Set up clustering, redundancy, high availability, and so on.

I would rate Microsoft Azure Cosmos DB a nine out of 10.

This is a good product and I recommend it, especially in cases where people want to keep their information outside of the organization and on the cloud. I would rate this solution a nine out of ten.

I am using the latest version of the solution. Overall, I would rate the solution at an eight out of ten. I have always been very happy with its capabilities. I would recommend the solution to other organizations.

Overall, on a scale from one to ten, I would give this solution a rating of seven. Aside from the scalability issues, we haven't experienced any other issues. I would recommend Cosmos. It made our lives a lot easier. There's not a big learning curve in order to understand the structure and how to use it. We were good to go with only one container. Anybody who is new can learn quickly.

Before implementing, know now how to use DocumentDB. Understand your use case. From an architecture perspective, we have a use case where we wanted to use more SQ and we used DocumentDB as the first consideration. There isn't a better SQL than DocumentDB available. Cloud provides this type of platform. The automatic performance is also very good. We did research on the internet and decided to go with DocumentDB. I would rate it an eight out of ten. Not a ten because there is what to be done for improvement. In the future, it should be simplified for developers so that it's not a hassle for them. There aren't many resources for SQL and DocumentDB. It may take time for more documentation to come out.