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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
September 2025
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Azure Data Lake Storage mindshare

As of September 2025, the mindshare of Azure Data Lake Storage in the Cloud Storage category stands at 1.3%, up from 0.2% compared to the previous year, according to calculations based on PeerSpot user engagement data.
Cloud Storage Market Share Distribution
ProductMarket Share (%)
Azure Data Lake Storage1.3%
NetApp Cloud Volumes ONTAP11.0%
Nasuni8.9%
Other78.8%
Cloud Storage

PeerResearch reports based on Azure Data Lake Storage reviews

TypeTitleDate
CategoryCloud StorageSep 14, 2025Download
ProductReviews, tips, and advice from real usersSep 14, 2025Download
ComparisonAzure Data Lake Storage vs NetApp Cloud Volumes ONTAPSep 14, 2025Download
ComparisonAzure Data Lake Storage vs Google Cloud StorageSep 14, 2025Download
ComparisonAzure Data Lake Storage vs Dropbox Business - EnterpriseSep 14, 2025Download
 
 
Key learnings from peers

Valuable Features

Azure Data Lake Storage is praised for its hierarchical namespace, strong security features, scalability, seamless integration with Azure services, and cost-effective storage options. Users highlight its flexibility, ease of use, and support for varied data types. Its security access policies, integration with tools like Databricks, and automated operations enhance usability for data handling, storage, and management, making it ideal for diverse data scenarios, particularly for those focused on big data analytics.
  • "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."
  • "Azure Data Lake Storage is user-friendly and easy to use."

Room for Improvement

Azure Data Lake Storage needs enhanced SAP connectivity and simpler APIs. Eastern European regions require Azure Storage Explorer integration. Improved instructions, comprehensive examples, and a clearer migration process are vital. Licensing clarity, support response times, and cost efficiency are major concerns. Better connector capabilities, format support, and version control are essential. AI features and user-friendliness could be improved. Faster throughput and flexible data retention periods would benefit users.
  • "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."
  • "Maybe the solution could be a bit more user-friendly."

ROI

Pricing

Azure Data Lake Storage users indicate a pay-as-you-go pricing model influenced by data volume and services utilized. While some find it expensive compared to other solutions, others highlight its affordability, especially in data storage. However, complex licensing models and variable costs depending on usage can pose challenges. The solution is noted for scalable options, though competitive positioning against AWS could be improved. Cost-effectiveness and pricing flexibility are recognized benefits.
  • "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 hierarchical storage of processed data, enabling efficient end-user access and analytics. They store raw and pre-processed data for data warehousing, reporting, and integration with tools like Databricks. It serves as a staging area for data scientists, supports secure storage with features like encryption, and facilitates large data handling. Its usage spans from storing JSON files and PDFs to managing multi-environment data integration and operational reporting.

Service and Support

Azure Data Lake Storage support varies. Some users avoid contacting support, relying on documentation and community resources. Others need assistance, particularly with integrations like Power BI. Initial support may lack expertise, requiring follow-ups. Response speed and quality generally rate highly, though some experience delays. Good documentation and clear instructions aid deployment. Users report that tickets are resolved quickly, with some finding third-party consultants beneficial. Support ratings range from seven to ten.

Deployment

Azure Data Lake Storage's initial setup varies in complexity. Some find it straightforward, while others face challenges due to project-specific needs or security configurations. Deployment time ranges from an hour to several weeks, often depending on automation and team expertise. Adequate knowledge of configurations and best practices is essential for success. Users appreciate the tool's flexibility across cloud, on-premises, and hybrid environments, though advanced users suggest improvements for secure configurations.

Scalability

Azure Data Lake Storage is highly scalable, handling large data efficiently. Users have mostly positive experiences, with some facing issues during migration. It supports a range of uses, including real-time setups and global transactions. Scalability varies based on complexity and integration with tools like Databricks. Many find it versatile, expandable, and customizable with hierarchical file structures. Some users note cost influences scalability. This storage is suitable for medium to large enterprises.

Stability

Azure Data Lake Storage is highly stable, frequently rated between eight and ten out of ten. Users express confidence in its reliability, only mentioning rare, brief outages. Stability depends on factors like settings and expertise. Many appreciate its good performance for data-focused tasks, despite an occasional issue, such as a past incident in October. The SLAs reflect high reliability, and users consistently indicate satisfaction with the stability and dependability.
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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Product Categories

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Azure Data Lake Storage Reviews Summary
Author infoRatingReview Summary
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.
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 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.
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.
Product Manager at AfroUrembo4.0I use Azure Data Lake Storage as our default data platform due to its simplicity in configuration and setup, along with good scalability for adding data. However, migrating data between lakes can be time-consuming and needs improvement.
Manager, Project at a consultancy with 1,001-5,000 employees4.5I use Azure Data Lake Storage as secondary storage for operational reporting and machine learning. The solution's reusable framework benefits multiple use cases, though costs increase due to Microsoft Fabric component charges. I prefer it for mid-sized companies.
Data Architect /Data Engineer at Regional Council4.5I use Azure Data Lake Storage to integrate diverse data sources into a unified platform. Although it lacks built-in features, it works well with Azure tools like Data Factory and Databricks. Supporting more formats, like Iceberg, would enhance its capabilities.
Associate Software Engineer at Systech Solutions4.0I use Azure Data Lake Storage for integrating data from HubSpot and Xero. Its versatility in storing various data types aids analytics. However, improving connectors to retrieve comprehensive data without relying on REST API calls would be beneficial.