What is Azure Data Lake?

Microsoft Azure provides storage in the cloud through its massive and scalable Data Lake Gen2 (Azure Data Lake) offering. Azure Data Lake supports data storage in various formats and data is always highly available.

Also, all data stored in data lake storage is encrypted. Data is authenticated through Azure Active Directory (AAD) and Role-Based Access Control (RBAC).

Data Lake Storage Gen2 offers hierarchical namespace which supports a nested directory structure for easy file access during data writes and reads. More information on this can be found on the Azure documentation page here.

What are key features of Azure Data Lake?

Data Lake Gen2 offers the following features for data storage:

• Containers: Data can be stored in several containers that scale vertically. Each container can have several directory and subdirectories with data stored in them. Containers accept almost any data format such as csv, text, parquet, media, etc.
• File shares: Data Lake Gen2 offers server-less file shares for sharing files across the Azure platform.
• Table Storage: Semi-structured data at massive scale can be stored in table storage. The table storage is ideal for NoSQL database design such as Azure Cosmos DB.
• Queue Storage: Queue storage is designed for communication between applications. Ideal for storing messages between applications.

Azure Data Lake supports storage redundancy to store multiple copies of data depending on the following options offered:

• LRS or Locally Redundant Storage
• ZRS or Zone Redundant Storage
• GRS or Geo Redundant Storage

Documentation on the storage redundancy options can be found on the Azure documentation page here.

Lastly, data from Data Lake Gen2 storage containers can be read into several compute resources within Azure (such as Databricks, Machine Learning Service, Synapse Analytics, etc.) and transformed data can be written back from several compute resources with ease. Data can also be ingested into Data Lake Gen2 storage using Azure Data Factory from several disparate sources including from on-premises.

Who is Azure Data Lake designed for?

Azure Data Lake is designed for organizations and teams who want to move and store big data from on-premises solutions to the cloud. Azure Data Lake is used by companies across various industries, all over the world.

What is Azure Data Lake?

Microsoft Azure provides storage in the cloud through its massive and scalable Data Lake Gen2 (Azure Data Lake). Azure Data Lake supports data storage in various formats and data is always highly available.

Also, all data stored in data lake storage is encrypted. Data is authenticated through Azure Active Directory (AAD) and Role-Based Access Control (RBAC).

Data Lake Storage Gen2 offers hierarchical namespace which supports a nested directory structure for easy file access during data writes and reads. More information on this can be found on the Azure documentation page here.

What are key features of Azure Data Lake?

Data Lake Gen2 offers the following features for data storage:

• Containers: Data can be stored in several containers that scale vertically. Each container can have several directory and subdirectories with data stored in them. Containers accept almost any data format such as csv, text, parquet, media, etc.
• File shares: Data Lake Gen2 offers server-less file shares for sharing files across the Azure platform.
• Table Storage: Semi-structured data at massive scale can be stored in table storage. The table storage is ideal for NoSQL database design such as Azure Cosmos DB.
• Queue Storage: Queue storage is designed for communication between applications. Ideal for storing messages between applications.

Azure Data Lake supports storage redundancy to store multiple copies of data depending on the following options offered:

• LRS or Locally Redundant Storage
• ZRS or Zone Redundant Storage
• GRS or Geo Redundant Storage

Documentation on the storage redundancy options can be found on the Azure documentation page here.

Lastly, data from Data Lake Gen2 storage containers can be read into several compute resources within Azure (such as Databricks, Machine Learning Service, Synapse Analytics, etc.) and transformed data can be written back from several compute resources with ease. Data can also be ingested into Data Lake Gen2 storage using Azure Data Factory from several disparate sources including from on-premises.

Who is Azure Data Lake designed for?

Azure Data Lake is designed for organizations and teams who want to move and store big data from on-premises solutions to the cloud. Azure Data Lake is used by companies across various industries, all over the world.