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.
Product | Market Share (%) |
---|---|
Azure Data Lake Storage | 1.3% |
NetApp Cloud Volumes ONTAP | 10.2% |
Nasuni | 8.5% |
Other | 80.0% |
Type | Title | Date | |
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Category | Cloud Storage | Oct 13, 2025 | Download |
Product | Reviews, tips, and advice from real users | Oct 13, 2025 | Download |
Comparison | Azure Data Lake Storage vs NetApp Cloud Volumes ONTAP | Oct 13, 2025 | Download |
Comparison | Azure Data Lake Storage vs Google Cloud Storage | Oct 13, 2025 | Download |
Comparison | Azure Data Lake Storage vs Dropbox Business - Enterprise | Oct 13, 2025 | Download |
Title | Rating | Mindshare | Recommending | |
---|---|---|---|---|
Dropbox Business - Enterprise | 4.1 | 8.3% | 90% | 90 interviewsAdd to research |
Iron Mountain Iron Cloud | 3.5 | 0.5% | 100% | 1 interviewAdd to research |
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?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.
Author info | Rating | Review Summary |
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DevOps Manager at a computer software company with 5,001-10,000 employees | 4.5 | I 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 employees | 4.5 | In 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 Solutions | 3.5 | We 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 employees | 4.0 | We 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 AfroUrembo | 4.0 | I 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. |
Associate Software Engineer at Systech Solutions | 4.0 | I 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. |
Senior Solutions Architect at EQ2 Technology | 5.0 | I 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. |
Enterprise Architect at a non-profit with 501-1,000 employees | 4.0 | Azure Data Lake Storage's valuable feature is its directory hierarchy for data partitioning, crucial for data delivery. We plan to convert data to Parquet format for Databricks use. Improvement is needed in converting input data formats out-of-the-box. |