Azure Cosmos DB vs. Azure Data Lake Storage

NoSQL platforms are very useful when it comes to security, speed, accuracy, high accessibility with high read and write power. Everything is managed under the cloud and we have the various capabilities of Azure and support for Microsoft products with us. Flexibility in price and variety of features, as well as real-time results, are some of the popular [features] of this platform.

Incentivized

Azure Data Lake storage is well suited for applications/use cases within organizations where capturing and storing large amounts of data in any format is required, primarily for storing and processing purposes. It's an easy and cost-effective cloud solution for your application data. The ability to integrate with other Azure Services like Azure Databricks and Azure Data Factory is superb.

Incentivized

• Turn-key geo-redundancy with multi-master writes is unprecedented and unparalleled in the industry!
• Guaranteed low latency makes Cosmos DB an excellent fit for most of our performance-intensive situations.
• The tunable consistency model simplifies so many challenges in distributed systems engineering that otherwise require advanced knowledge of computer science topics. I continue to be impressed at how Cosmos DB has abstracted away so much complexity.

Incentivized

• Azure Data Lake Storage is extremely scalable. It allows us to scale up or down endlessly based on what we need including replication.
• In terms of security, Azure Data Lake Storage fits our requirements really well as we can monitor and encrypt seamlessly. We can also assign permissions through roles and grant network-level access.
• Due to the fact that it can scale, we are able to monitor the cost of storage and any given time and make financial decisions about our infrastructure based on how small or big we want to scale.

Incentivized

• When searching by default, it is case sensitive, which must be changed by default
• In many ways, the price should be more flexible according to the requested facilities, because the price is very expensive for startup companies.
• It is not fully compatible with most common Streaming Analytics tools applications and developers should be worked on it

Incentivized

• I'd like to see a better cross-platform native client. Azure Data Explorer is fine, but it's far from the "SSMS" kind of experience SQL Server users are used to.
• Listing a large number of file is somewhat problematic and slow. Using the native C# library, running directly on an Azure VM, it can take several hours to list just a couple million files.
• Switching from V1 to V2 requires the creation of a new Storage Account and that's pretty inconvenient.

Incentivized

It's efficient, easy to scale, and works. We do have to do a bit of administration, but less now than when we started with this a couple of years ago. Microsoft continues to improve its self-management capability.

Incentivized

Like I said, Cosmos is the way to go. From all of the services that Azure has, Cosmos is very robust in terms of usability. It's ever-evolving and integrates with other applications seamlessly. The interface is pretty easy to understand. I implemented various solutions for my company and Cosmos was one of them.

Incentivized

The support team is very responsive and we are generally satisfied with Microsoft support, in my opinion support team of a product and service is just as valuable as its quality and performance. Telephone answering, 24-hour hotline, email support and ticketing are excellent.

Incentivized

Azure Cosmos DB for MongoDB is more affordable than many other solutions and works incredibly well if you're within the Azure ecosystem.

Incentivized

The Azure Data Lake solution is designed for organizations that want to take advantage of big data. It provides a data platform that can help developers, data scientists, and analysts store data of any size and format and perform all types of processing and analytics across multiple platforms and programming languages. It can work with your existing solutions, such as identity management and security solutions. It also integrates with other data warehouses and cloud environments. It can be useful for organizations that need the above softwares.

Incentivized

• Expensive but works if your infra is on Azure data center.
• No latency and nearly no downtime.
• Takes time for end users to adapt.

Incentivized

• The cost can be high for more advanced work. In some cases, for instance, time limits and lab runtimes may be too short if you are too slow to learn what is explained as you go along.
• promote flexible team communication. You can create different spaces for different teams, and share files and tasks.

Incentivized