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We use Microsoft Azure Cosmos DB as a NoSQL database to store JSON documents for our clients in the Banking, Financial Services, and Insurance sectors, primarily insurance. They require storage for numerous documents, including policy, claims, and costing documents, making Cosmos DB the ideal solution.

Because the company is spread across multiple regions, maintaining consistency with traditional relational databases was a challenge. Cosmos DB solved this by offering various consistency options and geo-replication capabilities. Logical partitioning within Cosmos DB improved routing efficiency, and composite indexes, combined with the partition key, optimized query execution by directing requests to specific documents, minimizing resource consumption.

Cosmos DB can offer faster data retrieval than SQL for certain queries and workloads, particularly those involving large volumes of unstructured or semi-structured data.

Cosmos DB is highly capable of handling large workloads and offers exceptional reliability for document storage and similar needs. Its particular strength lies in-stream analytics, a functionality currently not supported by MongoDB. This makes Cosmos DB the ideal solution for customers requiring real-time data processing, and it is our consistent recommendation for those working with stream analytics.

I appreciate Microsoft Azure Cosmos DB's robust document management and consistent availability. The databases are always operational, ensuring continuous accessibility and simplifying disaster recovery procedures. The geo-redundancy feature is particularly valuable, especially for European operations.

Cosmos DB needs improvement in a few areas, primarily the ability to join data across containers. Currently, it doesn't support cross-container joins, forcing developers to retrieve data from each container separately and combine it using methods like LINQ queries. This workaround is inefficient and cumbersome. A built-in join functionality would be a significant improvement. Additionally, Cosmos DB's SQL queries are susceptible to injection attacks due to limited parameter support. Currently, only one parameter can be used, compelling developers to use string interpolation, which introduces security risks. The ability to pass multiple parameters would enhance both security and code quality.

Sometimes, clients may lack technical expertise and run queries without utilizing partition keys, leading to significantly increased request units and higher costs. While Microsoft Azure Cosmos DB currently leads the market, enhancements are needed, particularly regarding data statistics across different containers. Dealing with clients who have multiple containers often requires custom code to stitch data together, highlighting the need for functionality supporting joins across containers. Additionally, a more stable and predictable pricing plan would benefit both developers and clients.

I have been using Microsoft Azure Cosmos DB for more than four years now.

Microsoft Azure Cosmos DB offers exceptional stability, boasting a reliability rating of 99.95 percent. This ensures continuous availability without downtime.

I rate the scalability of Cosmos DB highly, with a score of nine point five out of ten.

Microsoft's support services are inadequate, especially during critical incidents. The faster response times found in community-driven resources, such as Stack Overflow, underscore the shortcomings of Microsoft's customer support.

Negative

While Amazon DynamoDB offers extensive configurability, this can be time-consuming. For projects with tight deadlines requiring a NoSQL database, Cosmos DB is a preferable choice due to its ease of setup and minimal configuration. Additionally, Cosmos DB provides superior support for the Jira application and offers better uptime than DynamoDB.

The provided templates help us deploy Cosmos DB quickly.

Cosmos DB's billing is based on request units, which isn't ideal for all clients. Pricing plans offering set benefits, similar to Azure's platform resources, could be beneficial. The current method lacks clarity for clients new to cloud-native architectures, hindering migration from on-premises systems.

Billing is based on request units, so it's crucial to optimize queries to minimize consumption. A standard estimate is one to one point five request units for read requests and four to five for insert, update, or delete operations.

I would rate Cosmos DB's cost at seven out of ten, with ten being the highest.

Cosmos DB can provide improved search result quality, but we must understand the partition key of our container. Using the correct partition key in our queries ensures precise results. Without it, queries may consume excessive Request Units of over 5,000 and ultimately fail.

Microsoft Azure Cosmos DB is a strong product with the potential for improvement in supporting joins from different containers and providing more stable pricing plans. Despite these areas for growth, Cosmos effectively competes with services like AWS DynamoDB and currently leads the market. Overall, I rate the solution an eight out of ten.

Our Cosmos DB deployment spans across Europe, with the primary data center located in Italy to serve our European users. Additionally, we have another customer based in the eastern US, where their data is replicated across three data centers in the eastern US and three more in the western US for redundancy and high availability. We currently have 40 projects using Cosmos DB for clients in different industries ranging from oil and natural gas to sports and media.

We use Azure WebJobs to maintain our databases by removing expired policies and contracts. However, Microsoft should implement a similar system in Cosmos DB, utilizing its Hot and Cold Tier functionality for archival storage. This would allow us to efficiently move outdated data to archival storage, mirroring the functionality we have with Azure WebJobs.

Redis is used for a part of a booking engine for travel, specifically for the front part to get some sessions and information about the sessions. If a customer or user is using the sites in different parts, we use Redis to get this information in cache.

The best features of Redis, from my personal perspective, are the performance, which is very quick, and it's very simple to implement.

Since I started using Redis, I feel that the product is saving me some performance tuning time. It's very easy, I have few parameters to tune, and it seems to have performance without a lot of working on the performance, compared to Cassandra, where you have to configure the memory and many other settings.

The integration capability of Redis is excellent.

Redis is very affordable because it's free.

The disadvantage of Redis is that it's a little bit hard to have too many clusters or too many nodes and create the clusters. The sync between the nodes is easier to implement with Couchbase, for example, and this is the only problem, the only disadvantage for me.

I started using Redis this year.

The stability of Redis rates nine out of ten, with one being not stable and ten being very stable.

The scalability of Redis rates eight out of ten, with one being not scalable and ten being very scalable.

Technical support rates at three out of ten.

Neutral

We started using Redis this year when we switched from Couchbase at the beginning of the year.

I have decommissioned Couchbase, which was not my database but my customer's database. They decommissioned it this year and chose Redis for the cache data parts, so I'm not using Couchbase anymore.

We use community support and we don't have a provider for the support, but to be honest, we don't need support. From the time we implemented, I hope it will continue this way.

I see about 40% savings since using Redis.

In my projects, we use documents basically, so all the NoSQL databases can be mapped with an API to have a kind of independence from Redis and any tool. If tomorrow we want to move from Redis to something better, we are independent from that.

If Redis has questions or comments related to my review, it's possible for them to reach me via email to clarify something.

I am interested in being a reference for Redis.

On a scale of 1-10, I rate Redis a 10.