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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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Azure Data Lake Storage is the #9 ranked solution in top Cloud Storage solutions. PeerSpot users give Azure Data Lake Storage an average rating of 8.6 out of 10. Azure Data Lake Storage is most commonly compared to Dropbox Business - Enterprise: Azure Data Lake Storage vs Dropbox Business - Enterprise.
Buyer's Guide
Azure Data Lake Storage
January 2026
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Azure Data Lake Storage mindshare

As of January 2026, the mindshare of Azure Data Lake Storage in the Cloud Storage category stands at 1.4%, up from 0.7% compared to the previous year, according to calculations based on PeerSpot user engagement data.
Cloud Storage Market Share Distribution
ProductMarket Share (%)
Azure Data Lake Storage1.4%
Dropbox Business - Enterprise7.7%
NetApp Cloud Volumes ONTAP7.0%
Other83.9%
Cloud Storage

PeerResearch reports based on Azure Data Lake Storage reviews

TypeTitleDate
CategoryCloud StorageJan 27, 2026Download
ProductReviews, tips, and advice from real usersJan 27, 2026Download
ComparisonAzure Data Lake Storage vs Google Cloud StorageJan 27, 2026Download
ComparisonAzure Data Lake Storage vs Dropbox Business - EnterpriseJan 27, 2026Download
ComparisonAzure Data Lake Storage vs NetApp Cloud Volumes ONTAPJan 27, 2026Download
Suggested products
TitleRatingMindshareRecommending
Dropbox Business - Enterprise4.17.7%90%91 interviewsAdd to research
Google Cloud Storage4.34.3%97%80 interviewsAdd to research
 
 
Key learnings from peers

Valuable Features

Azure Data Lake Storage's valuable features include a hierarchical namespace enhancing performance, robust security access policies, great scalability, and a user-friendly interface. It supports diverse data types and integrates well within the Microsoft ecosystem, including tools like Databricks and Azure Data Factory. It offers cost-effective storage options, automated data operations, and comprehensive integration across Azure tools, providing connectivity and flexibility for various data management tasks.
  • "I would say the best features include that it's easy to integrate; it's certainly easy to integrate with the other things in the Microsoft portfolio."
  • "Azure Data Lake Storage offers comprehensive integration with a variety of Azure tools, such as SQL servers and the Azure DevOps platform."
  • "Azure Data Lake Storage is user-friendly and easy to use."

Room for Improvement

Azure Data Lake Storage needs improvement in pricing and support response speed. Users desire better integration with SAP systems, enhanced APIs, and clearer migration processes. Documentation and user-friendliness require enhancements, including tutorials and examples. The licensing model is complex, and format support could be expanded beyond current offerings. Users also want stronger security features, faster throughput, and out-of-the-box data conversion tools. Better integration options with other vendor solutions and improved connectors are crucial.
  • "There are some gotchas with the pricing; you have to be careful. There's not really a way to throttle it either."
  • "The speed of support response needs to improve, especially for critical, high-priority issues. Having a quick SLA response time is crucial."
  • "The scalability is limited. However, it's easy to set up."

Pricing

Azure Data Lake Storage uses a pay-as-you-go model, making costs variable based on data storage and service usage. While some users find it expensive, others see it as cost-effective compared to AWS, particularly for storage capacity. Pricing complexity is noted, often linked to Microsoft's licensing model. Storage is affordable, while computation costs can be higher. Pricing can fluctuate based on factors like location configuration and use cases like machine learning, influencing total costs.
  • "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

Azure Data Lake Storage is leveraged for storing pre-processed JSON files, data warehousing with Databricks and Hadoop, storing raw customer files, secure data transfer, aggregating information, creating diverse data storage types, and handling Big Data. It serves as a staging area for data scientists, supports PDF extraction for AI applications, facilitates call monitoring, and integrates with various Azure resources to manage large data volumes for analytics and reporting tasks.

Service and Support

Azure Data Lake Storage's support has mixed feedback. Some users find technical support knowledgeable and responsive, while others note initial support lacks expertise, requiring follow-up. Many rely on documentation, community support, or external consultants instead of Microsoft directly. Quick resolutions are appreciated; having clear instructions aids smooth deployment. Agreement type influences service speed, ranging from immediate to weeks. Microsoft documentation is praised, though many handle issues internally without needing direct support.

Deployment

Users describe Azure Data Lake Storage setup as varying in complexity. Some report a straightforward process completed in under an hour, while others face challenges requiring detailed knowledge and weeks of effort. Templates and automation aid deployment. Security configuration can be complex. Deployment depends on the project's scope, and experienced teams find it easier. Ratings for ease vary, with many rating it between seven and ten out of ten.

Scalability

Azure Data Lake Storage offers highly scalable capabilities, with user ratings averaging between six and ten. Many describe it as excellent, accommodating extensive data and a growing user base. Scalability depends on complexity, with better performance for simpler processes. Azure Data Lake Gen 2 and Gen 3 versions are particularly praised for flexibility. Some users highlight limitations in cross-region scaling or complex data structures but find data management efficient, utilizing complementary tools for enhanced performance.

Stability

Azure Data Lake Storage exhibits strong stability, frequently receiving ratings between eight to ten out of ten. Users have found it reliable and suitable for data applications, with minimal downtime and disruptions. Although there was a notable incident in mid-October affecting multiple businesses, such occurrences are rare. Configurations like geographical redundancy influence stability, and service-level agreements indicate significant dependability. Users appreciate its stability, noting few performance issues and no major crashes reported.
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.

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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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Azure Data Lake Storage Reviews Summary
Author infoRatingReview Summary
Vice President, Technology at a tech vendor with 11-50 employees4.5I’ve used Azure Data Lake Storage extensively for analytics with Databricks, and it's easy to integrate and set up, though pricing can be tricky and lacks flexibility; overall, it’s reliable, scalable enough, and fits well within the Microsoft ecosystem.
DevOps Manager at a computer software company with 5,001-10,000 employees4.5I use Azure Data Lake Storage for various data types and appreciate its seamless integration with Azure resources. Its valuable features like lifecycle management aid in data backup, but migration improvements and retention period extension are necessary. Competitors include AWS and Google Cloud Storage.
EPM Practice Manager at a tech services company with 1,001-5,000 employees4.0We implement solutions using Azure Data Lake Storage due to its integration with Azure tools such as SQL servers and Azure DevOps. While it's a robust platform, support speed for critical issues needs improvement for better efficiency.
Data Engineer at a financial services firm with 1,001-5,000 employees4.5In my use case, Azure Data Lake Storage is effective for storing PDF files for AI applications. It's cost-effective, integrates with Azure services, and offers hot and cold storage options. However, a vector database feature would enhance its AI capabilities.
Senior Solutions Architect at EQ2 Technology5.0I find Azure Data Lake Storage to be secure for data analytics and processing, supporting safe transfers via Azure Storage Explorer. Although its rapid improvements are impressive, enabling certain features in weaker IT environments can be challenging.
Senior Solutions Architect at Think Power Solutions3.5We use Azure Data Lake Storage for call monitoring and connecting data lakes, handling both structured and unstructured data for analytics. The scalability due to the blob is valuable, though adding AI features would enhance the solution.
Data Engineer at Universidad Peruana de Ciencias Aplicadas4.5In my experience with Azure Data Lake Storage, it optimizes storage and data processing with tools like Global Storage while reducing costs. However, data integrity needs improvement, and better security features could enhance its suitability for big data solutions.
BI & Data Engineering Manager at a sports company with 10,001+ employees4.5Azure Data Lake Storage ensures secure, seamless data integration with features like Azure BitLocker encryption. Its cost is decent, and its reliability, performance, and scalability are strong. Improvement could be made in integrating serverless query features with Data Lake Analytics.