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Azure Data Lake Storage Reviews

Vendor: Microsoft
4.3 out of 5
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What is Azure Data Lake Storage?

Azure Data Lake Storage is widely used for data warehousing, storing processed data, raw customer files, and integrating data from multiple sources, supporting analytics, reporting, and machine learning by securely storing JSON, CSV, and other formats.

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Buyer's Guide
Azure Data Lake Storage
October 2024
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Key learnings from peers

Valuable Features

Azure Data Lake Storage offers robust security features like SAS tokens and Row-Level Security, high scalability, speed, and a hierarchical namespace for optimized performance. It supports diverse data types and easy integration with tools like Azure Storage Explorer and Databricks. The solution promotes usability, efficient configuration, and management with policy options. Additionally, it facilitates data partitioning, standardization, and hybrid cloud directories, enhancing data analytics, storage, and accessibility.
  • "Storage within Azure Data Lake is cheaper, which is one of the reasons we moved to it."
  • "Azure Data Lake itself doesn't have built-in features for handling data on its own. It's used as a collection of data. Tools you can use with it include Azure Data Factory and Databricks."
  • "The tool offers a big storage layer. The security aspect is quite good. In Azure, there's an option for soft deletes and policy management. This allows us to store only the most up-to-date data while everything else can be policy-managed. This makes handling and management easier."

Room for Improvement

Azure Data Lake Storage could improve affordability, SAP system connectivity, API accessibility, integration capabilities, support quality, and provide clearer instructions and better migration paths. Enhancements in connector capabilities, faster data throughput, and features like out-of-the-box data conversion and serverless query integration are needed. Improving data security, licensing model simplification, and better regional support are also necessary.
  • "The documentation could be more user-friendly with better tutorials."
  • "Azure Data Lake Storage should support other formats apart from the Data Lake format, such as the Iceberg format."
  • "If I had to nitpick, maybe the throughput could be faster - how quickly you can access data and how fast data can be written onto the Azure Data Lake Storage."

ROI

Pricing

Azure Data Lake Storage uses a pay-as-you-go pricing model, with charges based on storage amount. Users find it cost-effective compared to AWS, with some rating it cheaper by 30%. Satisfaction with pricing is mixed; some find it quite expensive and complex due to Microsoft's evolving licensing model. Overall, while generally perceived as affordable, actual costs vary depending on usage and additional services like Microsoft Fabric.
  • "It costs just a few dollars per terabyte per month."
  • "Pricing is tricky because it depends on the solution you're building and the type of Data Lake storage you use—hot or cold."
  • "On a scale from one to ten, where one is cheap and ten is expensive, I rate the solution's pricing a seven out of ten."

Popular Use Cases

Organizations use Azure Data Lake Storage primarily for data storage and processing. Common use cases include storing pre-generated static data, raw customer files, and processed data from pipelines. It is also utilized for data warehousing, secure data transfer, operational reporting, machine learning implementations, and integrating data from various sources. Users leverage its security features, staging layers, and ability to aggregate data for reporting and analytics.

Service and Support

Customer service for Azure Data Lake Storage varies. Some users report smooth operation without needing support, while others have faced challenges requiring assistance, particularly with integrations like Power BI. First-level support expertise and responsiveness could improve. Users find Microsoft's documentation helpful, reducing the need for direct support. Quick and reasonable responses are noted when tickets are raised. Intermediate suppliers and external consultants also provide valuable expertise.

Deployment

The initial setup of Azure Data Lake Storage varies from being straightforward and taking under an hour to being moderately complex and requiring weeks. Deployment can be automated, use templates, or involve manual steps. Users emphasize the importance of security configurations and understanding the tool. Some rate the ease between five and ten out of ten, noting that proficiency and the project complexity affect setup time, ranging from hours to months.

Scalability

Stability

These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.
Download our Azure Data Lake Storage Buyer's Guide for additional reliable information.

Learn more about Azure Data Lake Storage

Organizations use Azure Data Lake Storage to aggregate information for reporting, integrate it into data pipelines, and benefit from secure transfer capabilities. It serves data scientists as a staging area and businesses leverage its Big Data capabilities for developing technological solutions. With strong security features, high scalability, hierarchical namespace for better performance, and efficient data partitioning, it integrates seamlessly with tools like Databricks. Supporting structured, unstructured, and semi-structured data, it is ideally suited for data lakes.

What are the key features of Azure Data Lake Storage?
  • Strong security features: Includes SAS tokens and access policies
  • High scalability: Able to manage vast amounts of data
  • Hierarchical namespace: Improves performance
  • Efficient data partitioning: Enhances data management
  • User-friendly configuration and integration: Supports tools like Databricks
  • Support for various data formats: Ideal for data lakes
What are the expected benefits and ROI?
  • Hybrid cloud directories: Enhances data management
  • Enhanced big data handling: Improves data analytics processes
  • Policy management for data retention: Facilitates compliance

Azure Data Lake Storage finds its application in several industries by enabling technological solutions that leverage its Big Data capabilities. For instance, businesses in finance use it for aggregating financial reports, while retail companies leverage it for customer data analytics. Healthcare industries use it to store and analyze patient data securely. The manufacturing sector benefits by integrating data from different sources to optimize production processes.

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