Amazon S3 is the leading platform for building data lakes, providing a scalable, cost-effective and durable solution. This article provides you the key features of data lake and the manage ways with Lake Formation, what’s more, offers you a comparison between Amazon S3 and Azure Data Lake.
A data lake is a central repository that helps you break down data silos and can maximize end-to-end data insights. And with Amazon S3's durability, availability, scalability, security, compliance, and auditing capabilities providing the foundation for a data lake, you can leverage AWS analytics services to support your data needs, from data ingestion, movement, and storage to big data analytics, streaming analytics, business intelligence, machine learning (ML), and more, all at the best price/performance ratio.
1. Decouple Storage from Compute and Data Processing
With Amazon S3, you can cost-effectively store all data types in a raw format. You can launch as many virtual servers as you need to run your analytics tools using Amazon Elastic Compute Cloud (Amazon EC2) and process data using services from the AWS Analytics portfolio.
2. Centralized Data Architecture
It’s easy for Amazon S3 to build a multi-tenant environment where multiple users can run different analytics tools against the same copy of data, which reduces costs and improves data management.
3. S3 Cross-region Replication
You can use the cross-regional replication feature to replicate objects between S3 storage buckets in the same account or even different accounts. This minimizes latency and improves operational efficiency.
Lake Formation provides mechanisms for enforcing management, semantic consistency, and access control over data lakes. It makes your data more amenable to analytics and machine learning, providing better value to your business. The following are some steps to set up a data lake with Lake Formation.
📌Note: Before starting with the Lake Formation, you need to have these preparations. ▶Create an AWS account. ▶Have an IAM user.
Step 1. To allow access to Lake Formation resources, set yourself as a data lake administrator, select Add myself, and then register an Amazon S3 path.
Step 2. Create a database in AWS Glue Data Catalog. In the Create database tab, enter the Database Name, Location, and click Create database.
Step 3. Grant permissions for AWS Glue.
Step 4. Grant access to the table data. Navigate to Table, and select Grant. And enter the information required: IAM users and roles, then select all the options in Table permissions tab.
Step 5. Query the data with Athena, first, choose Query Editor > Tables and select zip code table. Then choose Table Options > Preview table. Then into the Settings and click Manage.
Although Amazon S3 and Auzure Data Lake are popular solutions for building data lakes, they have different features and functionalities. The below table shows their differences.
|
Characteristic |
Amazon S3 |
Azure Data Lake |
|
Storage Type |
Object storage that allows unlimited data storage in various formats, suitable for a wide range of use cases. |
A hierarchical file system that enhances performance for big data analytics and supports both structured and unstructured data. |
|
Integration |
Seamless integration with AWS services such as AWS Glue, Amazon Athena, and Amazon Redshift |
Works with Azure services such as Azure Databricks, Azure Synapse Analytics, and Power BI. |
|
Data Management |
Provides data bucket policies, IAM roles, and S3 access points for data access management. |
Provides role-based access control (RBAC) and integration with Azure Active Directory for secure data access. |
|
Data Processing |
Data processing is supported through services such as AWS Glue and Amazon EMR. |
Optimized for big data processing using Azure Databricks and HDInsight. |
Amazon S3 is a powerful and flexible solution for building data lakes, but it also faces challenges such as cost management, complexity, and performance.
AOMEI Cyber Backup is a powerful and reasonable backup software designed to protect critical data, it offering comprehensive data protection features. With AOMEI Cyber Backup, you can enjoy more features.
😊User-friendly Interface: Simplify the backup process with an intuitive, easy-to-use interface. ⏰Automated Scheduling: You can schedule backups to run automatically at specific intervals. ✨Flexible Backup: It supports full, incremental, and differential backups. 🔐Secure Storage: Archive backups to Amazon S3 for protecting sensitive data. 📧Instant Reports: It offers email notifications for successful backups as well as errors or abnormalities.
1. Click Target Storage > Amazon S3 > +Add Target to open the add target page. Then enter Username, Password, and Bucket, and click Confirm.
2. Click Backup Task to Create New Task and start archiving your data to Amazon S3.
3. Select Archiving backup versions to Amazon S3 to choose the added Amazon S3 bucket.
4. Schedule backup tasks to run daily, weekly, or monthly, and choose backup retention policies to automatically delete old backups.
5. Select Start Backup to begin the backup process. It first creates backups locally or on a NAS and then uploads them to Amazon S3, ensuring the security of critical data and business continuity based on 3-2-1 backup rules.
To fully use the data for the enterprise, Amazon S3 provides a powerful platform to create a data lake. With a data lake, the enterprise can store and analyse massive data, which can encourage creativity and decision-making.