Azure Data Lake Storage

Secure, scalable, and cost-effective storage for big data analytics. Store any type of data, at any scale, with enterprise‑grade security and management features.

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Key Features

Massive Scalability

Petabytes of data with virtually unlimited storage capacity across regions.

Hierarchical Namespace

Organize data with directories and files for faster analytics and fine‑grained security.

Enterprise Security

Integration with Azure Active Directory, role‑based access control, and encryption at rest.

Cost Management

Pay‑as‑you‑go pricing, lifecycle policies, and tiered storage for optimal cost control.

Getting Started

Follow the steps below to create a Data Lake Storage Gen2 account and begin ingesting data.

1️⃣ Create a Storage Account

az storage account create \
    --name mydatalake \
    --resource-group MyResourceGroup \
    --location eastus \
    --sku Standard_LRS \
    --kind StorageV2 \
    --hierarchical-namespace true

2️⃣ Create a File System

az storage fs create \
    --name myfilesystem \
    --account-name mydatalake

3️⃣ Upload Data

az storage fs file upload \
    --account-name mydatalake \
    --file-system myfilesystem \
    --path raw/data.csv \
    --source ./data.csv

For a step‑by‑step walkthrough, see the Quickstart guide.

Sample Code (Python)

Use the Azure SDK for Python to interact with Data Lake Storage.

from azure.storage.filedatalake import DataLakeServiceClient

service = DataLakeServiceClient(account_url="https://mydatalake.dfs.core.windows.net",
                               credential="<account-key>")
filesystem = service.get_file_system_client("myfilesystem")
file_client = filesystem.get_file_client("raw/data.csv")

# Read file content
download = file_client.download_file()
print(download.readall().decode())