Azure Data Lake Store Reviews

It is our data storage layer. Where we store delta tables and parquet files images etc

It's a bit of pain to get it setup unlike lakehousese in Microsoft fabric

It is our data integration layer.

Azure Data Lake Store has been solid for handling high-volume data in our pipeline. We use it frequently for storing raw and processed data across different projects, and it scales well as our data grows. Integration with Azure Data Factory and Databricks makes implementation smoother and ease compared to setting things up from scratch. I also appreciate the access control flexibility through RBAC and ACLs.

Setting it up initially took some time, especially figuring out the permission structure and understanding the pricing breakdown. It wasn’t the most intuitive process. Customer support is responsive, but sometimes it takes a few back-and-forths to get to the root of a more technical issue. Also, during high-frequency usage, there have been rare moments of latency, especially when querying large files directly.

Azure Data Lake Store helps us manage and store massive volumes of structured and unstructured data in a centralized, cost-effective way. It solves the problem of scattered data sources and makes it easier to build a unified data platform for analytics and reporting. With its support for big data tools like Azure Data Factory, Synapse, and Databricks, we're able to process large datasets more efficiently. It has also improved our data governance by allowing granular access controls, which is especially useful when different teams need different levels of access.

.it is scalable, ease to use and implement,its cost efficient and easy to integrate with multiple soultion, it comes handy for use in case of processng data,

limited support for certain features, outdated document, some users faces inosistance

it helps me in resolving scalability challenges , we get high performance for data processsing, it helps in ensure data security meets compliance requirement

Easy to access, and provide analytics support and hirererica namespace

As a storage service i dont think there is any things to dislike

It is used to store large amount of daya , raw and yransformed data both.

We can store large amounts of data in structured and unstructured format. It's really helpful to store data

Nothing like that. It's helpful for all data engineer to store data

No such problem we faced during data storage

.Scalability,integration,security,compatibility and cost effective

Complexity,learning curve,performance tuning,cost

It is useful for storing client data

It is cheaper compared to database storage and has the capability to store different formats of files.

Azure Data Lake is costly if we want to use it with some other cloud provider services like AWS and GCP.

Since I work in a product based company, we have TB's of data which need to be stored and processed with analytics. Azure Data Lake storage is good service for us.

Scalable storage for big data analytics workloads. It offers unlimited storage capacity, allowing you to store and process large datasets efficiently.

Cost, complexity, Data management and not Compatible with all analytics tools and frameworks

It solves storing, managing, and processing large volumes of data.

It is designed to handle structured and unstructured data, including text, images, videos, log files, and more. It allows us to store data in its native format, eliminating the need for upfront data transformation or schema enforcement.

.We can use data lake store to get AI and ML models to execute

Configurations are a little bit complex to use

Maintaining the stream data in data lake store

Speed don't reduced on data size increase

Support parallel processing

Easy to integrate with other data sources

There is no limit of data size