Are you trying to derive deeper insights from your Amazon DynamoDB by moving the data into a larger Database like Amazon S3? Well, you have landed on the right article. Now, it has become easier to replicate data from DynamoDB to S3 using AWS Glue.
This article will give you a brief overview of Amazon DynamoDB and Amazon S3. You will also get to know how you can connect your DynamoDB to S3 using AWS Glue. Moreover, the advantages and disadvantages of this method will also be discussed in further sections. Read along to decide which method of connecting DynamoDB to S3 is best for you.
Table of Contents
- What is Amazon DynamoDB?
- What is Amazon S3?
- What is AWS Glue?
- Steps to Connect DynamoDB to S3 using AWS Glue
- Advantages of Connecting DynamoDB to S3 using AWS Glue
- Disadvantages of Connecting DynamoDB to S3 using AWS Glue
You will have a much easier time understanding the steps to connect DynamoDB to S3 using AWS Glue if you have gone through the following aspects:
- An active AWS account.
- Working knowledge of Databases.
- Clear idea regarding the type of data to be transferred.
What is Amazon DynamoDB?
Amazon DynamoDB is a document and key-value Database with a millisecond response time. It is an internet-scale Database that is fully managed, multi-active, multi-region, and durable, with built-in security, in-memory caching, backup, and restoration. For essential activities, companies like Airbnb, Toyota, Samsung, Lyft, and Capital One rely on DynamoDB’s performance and scalability.
Some of the use cases of DynamoDB include:
- Dynamodb is heavily used in e-commerce since it stores the data as a key-value pair with low latency.
- Due to its low latency, Dynamodb is used in serverless web applications.
To know more about Amazon DynamoDB, visit this link.
Load Data From DynamoDB and S3 to a Data Warehouse With Hevo’s No Code Data Pipeline
Hevo Data, an Automated No-code Data Pipeline, helps you directly transfer data from Amazon DynamoDB and S3 to Data Warehouses, Databases, or any other destination of your choice in a completely hassle-free manner. Hevo’s fully managed pipeline uses DynamoDB’s data streams to support Change Data Capture (CDC) for its tables and ingests new information via Amazon DynamoDB Streams & Amazon Kinesis Data Streams. Hevo also enables you to load data from files in an S3 bucket into your Destination database or Data Warehouse seamlessly. Moreover, S3 stores its files after compressing them into a Gzip format. Hevo’s Data pipeline automatically unzips any Gzipped files on ingestion and also performs file re-ingestion in case there is any data update.Get started with hevo for free
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What is Amazon S3?
Amazon Simple Storage Service (Amazon S3) is a web-based cloud storage service that provides high-speed, scalable storage. It was created to back up and archive applications and data on Amazon Web Services.
Amazon S3 is a very useful tool since it allows users to store and retrieve data from anywhere on the internet at any time. This is done using the AWS Management Console, which has a user-friendly online interface. For example, Amazon utilizes S3 to host its websites all over the world. The popularity of S3 is rapidly increasing.
Some of the use cases of Amazon S3 include:
- Since S3 is cost-effective, S3 can be used as a backup to store your transient/raw and permanent data.
- Using S3, a Data Lake can be built to perform analytics and as a repository of data.
- S3 can be used in Machine Learning, Data profiling, etc.
To know more about Amazon S3, visit this link.
What is AWS Glue?
AWS Glue is a serverless ETL service, which is fully managed. Since it is serverless, you do not have to worry about the configuration and management of your resources. Before going through the steps to export DynamoDB to S3 using AWS Glue, here are the use cases of DynamoDB and Amazon S3.
To know more about AWS Glue, visit this link.
Hevo, a No-code Data Pipeline, helps customers move all their data into their preferred Data Warehouse without having to write any code. With a fault-tolerant architecture and exceptional security, Hevo automates a lot of your data processing tasks. Naturally, many users have already made the move from Glue to Hevo. So, what are you waiting for? Visit our website to explore more.
Steps to Connect DynamoDB to S3 using AWS Glue
This blog post details the steps to move data from DynamoDB to S3 using AWS Glue. This method would need you to deploy precious engineering resources to invest time and effort to understand both S3 and DynamoDB. They would then need to piece the infrastructure together bit by bit. This is a fairly time-consuming process.
Now, let us export data from DynamoDB to S3 using AWS glue. It is done in two major steps:
Step 1: Create a Crawler
The first step in connecting DynamoDB to S3 using AWS Glue is to create a crawler. You can follow the below-mentioned steps to create a crawler.
- Create a Database DynamoDB.
- Pick the table CompanyEmployeeList from the Table drop-down list.
- Let the table info gets created through crawler. Set up crawler details in the window below. Provide crawler name as dynamodb_crawler.
- Add database name and DynamoDB table name.
- Provide the necessary IAM role to the crawler such that it can access the DynamoDB table. Here, the created IAM role is AWSGlueServiceRole-DynamoDB.
- You can schedule the crawler. For this illustration, it is running on-demand as the activity is one-time.
- Review the crawler information.
- Run the crawler.
- Check the catalog details once the crawler is executed successfully.
Step 2: Exporting Data from DynamoDB to S3 using AWS Glue
Since the crawler is generated, let us create a job to copy data from the DynamoDB table to S3. Here the job name given is dynamodb_s3_gluejob. In AWS Glue, you can use either Python or Scala as an ETL language. For the scope of this article, let us use Python
- Pick your data source.
- Pick your data target.
- Once completed, Glue will create a readymade mapping for you.
- Once you review your mapping, it will automatically generate python code/job for you.
- Execute the Python job.
- Once the job completes successfully, it will generate logs for you to review.
- Go and check the files in the bucket. Download the files.
- Review the contents of the file.
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These are some benefits of having Hevo Data as your Data Automation Partner:
- Exceptional Security: A Fault-tolerant Architecture that ensures Zero Data Loss.
- Built to Scale: Exceptional Horizontal Scalability with Minimal Latency for Modern-data Needs.
- Built-in Connectors: Support for 100+ Data Sources, including Amazon DynamoDB, S3, and other Databases, SaaS Platforms, Files & More. Native Webhooks & REST API Connector available for Custom Sources.
- Data Transformations: Best-in-class & Native Support for Complex Data Transformation at fingertips. Code & No-code Flexibility is designed for everyone.
- Smooth Schema Mapping: Fully-managed Automated Schema Management for incoming data with the desired destination.
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With continuous real-time data movement, ETL your data seamlessly to your destination warehouse with Hevo’s easy-to-setup and No-code interface. Try our 14-day full access free trial.Sign up here for a 14-day free trial!
Advantages of Connecting DynamoDB to S3 using AWS Glue
Some of the advantages of connecting DynamoDB to S3 using AWS Glue include:
- This approach is fully serverless and you do not have to worry about provisioning and maintaining your resources
- You can run your customized Python and Scala code to run the ETL
- You can push your event notification to Cloudwatch
- You can trigger the Lambda function for success or failure notification
- You can manage your job dependencies using AWS Glue
- AWS Glue is the perfect choice if you want to create a data catalog and push your data to the Redshift spectrum
Disadvantages of Connecting DynamoDB to S3 using AWS Glue
Some of the disadvantages of connecting DynamoDB to S3 using AWS Glue include:
- AWS Glue is batch-oriented and does not support streaming data. In case your DynamoDB table is populated at a higher rate. AWS Glue may not be the right option
- AWS Glue service is still in an early stage and not mature enough for complex logic
- AWS Glue still has a lot of limitations on the number of crawlers, number of jobs, etc.
Refer to AWS documentation to know more about the limitations.
Hevo Data, on the other hand, comes with a flawless architecture and top-class features that help in moving data from multiple sources to a Data Warehouse of your choice without writing a single line of code. It offers excellent Data Ingestion and Data Replication services. Compared to AWS Glue‘s support for limited sources, Hevo allows you to set up data integration from 100+ Data Sources (including 30+ Free Data Sources). On top of that, Hevo offers you a flexible and transparent pricing plan where you don’t have to pay for storage and infrastructure.
AWS Glue can be used over AWS Data Pipeline when you do not want to worry about your resources and do not need to take control over your resources ie. EC2 instances, EMR cluster, etc. Thus, connecting DynamoDB to S3 using AWS Glue can help you to replicate data with ease. Now, the manual approach of connecting DynamoDB to S3 using AWS Glue will add complex overheads in terms of time, and resources. Such a solution will require skilled engineers and regular data updates. Furthermore, you will have to build an in-house solution from scratch if you wish to transfer your data from DynamoDB or S3 to a Data Warehouse for analysis.
Hevo Data provides an Automated No-code Data Pipeline that empowers you to overcome the above-mentioned limitations. Hevo caters to 100+ Sources & BI tools (including 40+ free sources) and can seamlessly transfer your S3 and DynamoDB data to the Data Warehouse of your choice in real-time. Hevo’s Data Pipeline enriches your data and manages the transfer process in a fully automated and secure manner without having to write any code. It will make your life easier and make data migration hassle-free.Learn more about Hevo
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Share your experience of setting up DynamoDB to S3 Integration in the comments section below!