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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
November 2024
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Helped 814,649 peers since 2012

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Key learnings from peers

Valuable Features

Azure Data Lake Storage's most valuable features include robust security, high scalability, and a hierarchical namespace for improved performance. Users appreciate its integration with tools like Databricks and Azure Data Factory. It supports various data types and allows flexible data partitioning. Organizations find it cost-effective with seamless storage management. Users experience ease with setup and configuration, alongside strong access control and data manipulation capabilities, enhancing data operations and workflows.
  • "The hierarchical structure allows us to create multiple hierarchies inside, such as storage containers, directories, and subdirectories."
  • "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."

Room for Improvement

Azure Data Lake Storage users suggest improvements in pricing and direct SAP connectivity. They seek enhanced API accessibility, simplified migration, comprehensive connector support, and better documentation. Users also desire improved data integrity, faster throughput, simplified licensing, and compatibility with non-Azure platforms. Enhancements in support, user instructions, security integration, and feature offerings like version control and format support are requested to optimize usage for big data solutions.
  • "Version control would be a great improvement."
  • "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."

ROI

Pricing

Azure Data Lake Storage utilizes a pay-as-you-go model, appealing for its affordability in large storage capacities. Some users consider the pricing to be reasonable, though others feel it's on the higher side compared to alternatives like AWS. The complexity of Microsoft's evolving licensing model is noted as a drawback. Pricing varies with usage; costs can rise with extensive features or computational use. The tool remains competitive due to its cost-effectiveness for storage compared to AWS.
  • "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 utilize Azure Data Lake Storage for hierarchical storage of static data, data warehousing, and file aggregation. It functions as a staging area for data migration and integration for analytics and reporting, with secure transfers via Azure Storage Explorer. Companies use it for storing raw files, processed data, and supporting machine learning workflows. Data is often moved into SQL Server or other formats, using tools like Databricks for processing and ETL tasks.

Service and Support

Many report smooth experiences without needing assistance, but others encounter challenges with initial support lacking expertise. Response times vary, often depending on agreements with Microsoft or third-party experts. Some leverage community help or extensive documentation instead of contacting support. Technical support is generally rated highly by those who use it, with ratings ranging from eight to ten out of ten. Ensuring setup resources are available is crucial for easier management.

Deployment

Users experienced varying levels of difficulty with Azure Data Lake Storage's initial setup. Some found it easy and efficient by utilizing templates or automated processes, while others encountered challenges due to complex security configurations and the need for detailed knowledge. Timelines ranged from under an hour to several weeks, influenced by factors like folder structure planning, resource needs, and security measures. Proper knowledge and planning improved the setup experience significantly.

Scalability

Azure Data Lake Storage is regarded as highly scalable by many users. Ratings for scalability range from six to ten. It handles large data volumes efficiently, with some users highlighting its compatibility with Databricks for enhanced performance. Experiences with scalability vary, influenced by data process complexity and architecture. Gen 2 and Gen 3 versions are noted for flexibility and integration capabilities. Many organizations, including global enterprises, find its scalability advantageous.

Stability

Stability for Azure Data Lake Storage is highly rated with most users giving it between eight and ten out of ten. Although some experienced a major issue in mid-October affecting businesses briefly, Azure is seen as reliable and performs well without significant interruptions. SLAs indicate strong performance, and despite rare brief outages, users find it dependable for data applications. Stability varies on settings and enterprise commitment to certain features.
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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