Azure Data Lake Storage

Azure Data Lake Storage

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Score 8.5 out of 100
Azure Data Lake Storage

Overview

Recent Reviews

For Big Data and Analytics

8 out of 10
April 07, 2022
If you need big data analytics for your structured, semi-structured, or unstructured data you can use Azure Data Lake Storage. It provides …
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Pricing

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What is Azure Data Lake Storage?

Azure Data Lake Storage Gen2 is a highly scalable and cost-effective data lake solution for big data analytics. It combines the power of a high-performance file system with massive scale and economy to help you speed your time to insight. Data Lake Storage Gen2 extends Azure Blob Storage…

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What is Azure Blob Storage?

Microsoft's Blob Storage system on Azure is designed to make unstructured data available to customers anywhere through REST-based object storage.

What is Cloudera Manager?

Cloudera Manager is a management application for Apache Hadoop and the enterprise data hub, from Cloudera.

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Product Details

What is Azure Data Lake Storage?

Azure Data Lake Storage Gen2 is a highly scalable and cost-effective data lake solution for big data analytics. It combines the power of a high-performance file system with massive scale and economy to help you speed your time to insight. Data Lake Storage Gen2 extends Azure Blob Storage capabilities and is optimized for analytics workloads.

Azure Data Lake Storage Technical Details

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Reviews and Ratings

 (35)

Reviews

(1-16 of 16)
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Abhishek Katara | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Stored Terabytes of Healthcare data in a cost-optimized solution on-cloud using Azure Data Lake Storage Gen2 in containerized fashion. We utilized Azure Data Lake Storage containers as a Destination in our Data Engineering Streasmets Pipelines. Loaded Data became available further to multiple downstream applications in an automated and faster way using Azure Data Factory. Also turned out a better, cost-optimized, and faster solution than HDFS for our different business use cases like the migration of huge data from RDBMS to Data Lake.
  • Setting up Azure Data Lake Storage account, container is quite easy
  • Access from anywhere and easy maintenance
  • Integration with Azure Data Factory service for end to end pipeline is pretty easy
  • Can store Any form of data (Structured, Unstructured, Semi) in faster manner
  • UI search feature can certainly be improvised e.g. inclusion of wildcards to search a particular file in container
  • Sometimes gets Hanged/lagged while monitoring
  • Probably the new UI feature can address above issues.
Azure Data Lake storage is well suited for applications/use cases within organizations where capturing and storing large amounts of data in any format is required, primarily for storing and processing purposes. It's an easy and cost-effective cloud solution for your application data. The ability to integrate with other Azure Services like Azure Databricks and Azure Data Factory is superb.
Score 3 out of 10
Vetted Review
Verified User
Review Source
We had all of our storage located within a single datacenter, which caused an issue should it go down. Azure Data Lake Storage allowed us to move some of the storage there, keeping that piece online and active if we lost communication to the main datacenter. It's nice, but not the most reliable.
  • PowerShell integration
  • Azure AD integration
  • AdlCopy
  • Price is a bit steep
  • CLI could be better
  • Permissions are difficult to use compared to their competition
Azure Data Lake Storage is great if it's used in a company where once configured no one goes in and make changes, and there is little to no need for growth over time. If it's a business that will be modifying it daily and constantly expanding, other vendors may have a more feasible option available.
Daniel Ortiz | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Overall it is easy to learn and would be useful for any home care service. Another thing that I like about it is that there is a phone call system where they help you with all the questions you may have. Audio and video calls are possible, with PC screen sharing its other systems Allows saving documents for some members or sharing them in general channels
  • Provides an overview of any device you will eventually work with in the future.
  • Having short videos allows me to go back and study precisely the topics I need without sifting through 30-minute videos to find the vignettes I need.
  • study for the certifications also to have them as a reference for work when you have any questions about applying a configuration to the equipment.
  • The Internet interface is simple and easy to use. Capacity is good and it's good that HP continues to innovate with this technology
Having short videos allows me to go back and study precisely the topics I need without sifting through 30-minute videos to find the vignettes I need. Using the labs, I got Associate Developer and Cloud Practitioner authorization. study for the certifications also to have them as a reference for work when you have any questions about applying a configuration to the equipment.
Score 9 out of 10
Vetted Review
Verified User
Review Source
In our environment, we use Azure Data Lake Storage as a basis for data analytics workflows. Since we want to move away from single storage solutions we chose Azure Data lake as it integrates seamlessly with our current Azure environment. We are able to process large amounts of data and visualize and present it accordingly while ensuring availability and security.
  • Azure Data Lake Storage is extremely scalable. It allows us to scale up or down endlessly based on what we need including replication.
  • In terms of security, Azure Data Lake Storage fits our requirements really well as we can monitor and encrypt seamlessly. We can also assign permissions through roles and grant network-level access.
  • Due to the fact that it can scale, we are able to monitor the cost of storage and any given time and make financial decisions about our infrastructure based on how small or big we want to scale.
  • Since the price of Azure Data Lake will fluctuate based on storage size we have to keep a close eye on what data is getting pulled in which can be a cumbersome task as data collection streams need to be throttled to prevent higher storage costs.
  • When we want to change the parameters of the data being captured by Azure Data Lake we have to keep in mind the historical data that's already been stored and consider methods for reprocessing it.
  • Azure Data Lake can improve its process for distorted data. As data gets loaded the data cleansing process can be a bit more refined.
Azure Data Lake is best suited for organizations looking to capture large amounts of data to process and store it. Azure Data Lake will make this process easy and cost-effective as it allows you to also report on this data. It provides tools to clean and present it into tables, charts, and graphs, and will easily integrate with any existing Azure environments.
Davide De Pretto | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
We need to store large amount of data that flow daily from our processes as well from external APIs, and we need to keep them for long period of times to perform historical analysis for our clients. Azure Data Lake Storage helps us achieve this goal by providing a secure, fast and large data store for our needs.
  • Store large amount of data
  • Access this data quickly using Synapse Analytics or Spark/Databricks
  • Ingest data quickly so our ingestion APIs are never throttled
  • I'd like to see a better cross-platform native client. Azure Data Explorer is fine, but it's far from the "SSMS" kind of experience SQL Server users are used to.
  • Listing a large number of file is somewhat problematic and slow. Using the native C# library, running directly on an Azure VM, it can take several hours to list just a couple million files.
  • Switching from V1 to V2 requires the creation of a new Storage Account and that's pretty inconvenient.
You should use Azure Data Lake Storage if you need to store large amount of data for analytical purposes, especially if combined with analytical solutions that support its API, like Azure Databricks or Azure Synapse Analytics. You should not use it for transactional workload, of course.
Score 9 out of 10
Vetted Review
Verified User
Review Source
As part of Analytics and BI COE within my company Azure Data Lake Storage has been a key ETL and data integration platforms to perform proper processing of huge amount of structured and semi structured data. Azure Data Lake is used as a test ground for creating use cases around integration of Azure Storage, MS SQL Server, Azure Synapse Analytics and for dynamic data using Azure Streaming Analytics
  • Well integrated connectors to third party storage sources
  • Robust and modular integrity within deployment pipeline
  • Helps resolve data storage both structured and unstructured
  • Improvement around spark integration
  • A single deployment pool to address both normal data and big data
  • Data Governance is still not centralized
When working with different data sources for a unified view data lake storage is a very robust platform and gives a easy way of managing different data and there resources. Scenarios with analysis on historical data can be achieved by archieving older data with Azure Dara Lake Storage and can be used to separate development, testing and production environment by the means of git integration within platform
Score 9 out of 10
Vetted Review
Verified User
Review Source
We use the Azure Data Lake Storage unlimited capacity for storing real big IoT data. The major problem with the real-time data is the scalability and when the business demands more resources the database e.g. increasing number of connected sensors, the Azure Data Lake Storage is highly scalable and helps us to manage such big data.
  • Scalable (hosted in the cloud)
  • Reliable
  • Fast
  • Cannot use blob APIs and NFS 3.0
  • Access controls
  • Handling unstructured data
For handling big data, it works very well, the interface is friendly also it provides a great feature and capability for adding security layers in working with data, so good security features.
The big data compute clusters are easy to set up and the learning curve is somehow easy but still Microsoft needs to provide more intractive instructions.
Score 9 out of 10
Vetted Review
Verified User
Review Source
Azure Data Lake Storage is a huge storage repository service that can be used to store information in the public cloud by Microsoft.
Our business scope is to work on a large data analytic project where we have to extract a large amount of structured and unstructured data for the data analysis and transformation.
Since we are also hosted our business application on Azure Cloud, the Azure Data Lake Storage is very helpful to use as it can be integrate with other Azure services and we do our analysis on the real-time at one place. Azure Data Lake Storage is built on the Hadoop file system which means it can process massive pentabytes of data in an efficient way.
It helps in streamline the overall efficiency of our requirement and business outcomes.
Except for some query performance improvements, we have faced no issues so far.
  • Provides significant performance and security measurements for analytical workloads.
  • Quickly process the queries and store large data.
  • Supports wide range of file extensions system.
  • Secured and scalable data storage solution.
  • Limitation in connecting with other non-Azure sources.
  • Performance issues with large datasets.
  • Improvements in bulk data update and deletion.
  • Query performance for exploratory data analysis.
Azure Data Lake Storage is built to help with large data analytics and transformations. It can be used as a single data repository for any structured and unstructured data extracted from almost any source. As it is built on top of the Hadoop file system (HDFS), jobs' overall analytic performance and running is quite impressive.
As some features are still in development phase, there are some improvements required to make this a unified storage solution for the organizations.
Steve Lollar | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Azure Data Lake is being utilized in a number of ways for our company, most of all tracking employee meal plans, and other analytical sales data. This is the best solution for our use case, and has worked extremely well. We love that it also integrates with Power BI, which our sales team and marketing folks use heavily.
  • Affordable and cost effective for small-medium sized businesses.
  • Regulatory Compliance Metrics
  • Deployment that's not complicated
  • U-SQL is somewhat complex to understand
  • You cannot use blob APIs, NFS 3.0, and Data Lake Storage APIs to write to the same instance of a file.
  • The WASB driver experiences issues all the time
ADL is great for structured and unstructured data backups: files, folders, disks, VMs, and databases. It does this better than any platform we ever vetted, and Microsoft is the industry standard typically.

It may not be feasible or cost effective if you don't have that much data to implement, or if you're a smaller organization with two or less VMs/production servers.
Score 8 out of 10
Vetted Review
Verified User
Review Source
Azure data lake storage performs very fast and it's cost effective. We can store the data in multi structure format and unstructured format. Azure data lake storage is easy to use and transform data using pipelines. The another good thing is It's support One Drive for Enterprise, SharePoint Online and Exchange online.
  • It's very fast and cost effective.
  • Strong support, good performance and scalability
  • Easy Integration with Databricks
  • Costing of Azure data lake store is very high and maintenance is also high for small companies
  • There are so many components and It's takes some time to fully understand it.
Azure data lake storage is best tool where you need to manage lot's of data. They provide so many good features and good customer support. It's easily integration with different services. Costing of Azure data lake store is very high and maintenance is also high for small companies.
Score 8 out of 10
Vetted Review
Verified User
Review Source
If you need big data analytics for your structured, semi-structured, or unstructured data you can use Azure Data Lake Storage. It provides us with unlimited storage. So we can use it to store any type of data of any size.
  • Usefull for big data analytics.
  • It is provide unlimited storage.
  • You can use any type of data or any size.
  • Easy to build structure
  • Easy to point any of batch in your big data
  • Data import or exporting progress can be faster
  • Maybe can add some detailed summary graphs for reporting
We are collecting data from our devices that are on the market. However, this amount of data is very big. Azure Data Lake Storage provides us with easy storage and analytics chance.
Score 7 out of 10
Vetted Review
Verified User
Review Source
We use Azure Data Lake Storage as a repository for our larger data analytics. Azure Data Lake has enabled us to capture data of various sizes (from small to large) and types, relatively fast for us to do our analytics. It integrated without issue into our existing data warehouses. Was able to set it up with minimal help.
  • File Storage
  • Highly Scalable
  • Cross Platform Support
  • Secure
  • Not as flexible as a data warehouse.
  • Not as optimized for queries as a data warehouse.
  • Could use more documentation.
While I did not think it was the most difficult to deploy, I did feel that there were some steps that took time when migrating from our data warehouse to data lakes. More documentation would have been helpful but I expect this to improve as the user base grows. I find that I need to be more careful in writing my queries for optimization when using a data lake. Can be a little more cavalier in a warehouse.
Score 7 out of 10
Vetted Review
Verified User
Review Source
Microsoft Azure Data Lake Storage is the best among all available Hadoop data Software in the market. It has the best end-to-end security for our data. It is used by our company to analyze our large data. It is highly cost-efficient and also highly scalable with gives us a visualization of our dataset and makes it easy to understand the data properly.
  • Data Visualization
  • Highly Encrypted
  • Cost Efficient
  • UI Design is quite complex to understand.
  • All Features are not up to date.
  • Analyzing large data sometimes makes its slow.
We have used Azure Data Lake Storage to analyze our large dataset to understand and visualize it thoroughly. It is highly encrypted and is highly scalable. It helps us to organize our data well and distribute it basis on its size.
Score 10 out of 10
Vetted Review
Verified User
Review Source
We use Azure Data Lake Storage for our big data analytics tasks across a variety of clients and data sets that are larger than the average sets.
  • Affordability
  • Security
  • Flexible semantic file systems
  • Hadoop integration
  • Scalability
  • None that I can remember.
Azure Data Lake Storage is great and affordable for anyone needing to process large data sets with better flexibility when it comes to file systems, looking for scalability and added file-level security, as well as other features like Hadoop integration amongst others.
Score 8 out of 10
Vetted Review
Verified User
Review Source
We used Azure Data Lake Storage to provide our enterprise with a medium to ingest and build our data warehouse. We went with the Azure storage because of our existing Microsoft footprint as well as the cost of the solution. After our initial discovery, we found that the tool was very easy to implement and we've been on it for 2 generations.
  • Ease of integration and setup
  • Support for the MS Suite of Applications
  • Extensible and upgradable
  • Switch in Gen 1 to Gen 2 was a bit tricky.
  • It can be performance bound if not properly architected.
  • Need to be incremental in how you implement.
Azure Data Lake Storage was our first project using a true data lake concept. In our experience it was a great product as it was easy to implement and matched our footprint quite well. After our initial work and the improvements Microsoft worked on, it became a better tool for us to run our reports and ingest our data.
Score 8 out of 10
Vetted Review
Verified User
Review Source
The product is pretty good. Asked in online communities to get more information from vendors on demonstrating capabilities, possible use cases, and how others are using it but not had good results. There are many components to their AZURE analytics solution, just takes time to understand how all the pieces work together.
  • The data lake analytics tool is good and provides loads of computing power to speed up the processing time.
  • It provides unlimited storage for structured, semi-structured or unstructured data.
  • Cloud-based service and we can easily use it for ETL and ELT processes.
  • It works well within the Azure ecosystem but still lacks connectivity from a lot of third-party tools.
  • Connectivity to and from multiple non Azure sources and targets is very limited.
  • Missing support from vendor.
Azure Data Lake is an absolutely essential piece of a modern data and analytics platform. Over the past 2 years, our usage of Azure Data Lake as a reporting source has continued to grow and far exceeds more traditional sources like MS SQL, Oracle, etc.
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