Azure Data Lake Storage vs. Cloudera Manager

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

Cloudera Manager is well suited for environments and deployments where the administrator user base is not well versed in the Apache Hadoop ecosystem or the Linux command line interface.

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

• Cloudera Manager has an easy to use web GUI. You can start and stop cluster and services. It will start and stop services in a cluster in the right order. You can monitor the cluster, services, and physical host hardware as well.
• Cloudera Manager has an easy to use API that allows us to create scripts to automate deployment process.
• Cloudera Manager has an option to add additional services that you could manage via the web GUI.

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

• Support for third-party Python APIs within Cloudera Manager extension framework
• Providing more reporting/logging functionality as part of the open source distribution
• Support for the latest RHEL versions sooner in the release lifecycle

Incentivized

It meets all my customer's needs.

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

I have not used any competitors, such as Hortonworks, because Cloudera Manager just works and meets all my customer's needs. I only have deployed Hadoop using command line, which is not easy to use and manage.

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

• Cloudera Manager has allowed our organization to deploy Apache Hadoop to operations quicker and with less training versus using the command line exclusively.
• Increased employee efficiency.
• Increased product adoption.

Incentivized