DynamoDB PostgreSQL Migration: 2 Easy Methods

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Organizations are migrating from on-premises databases and analytics solutions to the cloud in the modernization process. In keeping with the most recent forecast by Gartner Inc, the year 2021 has seen a growth of 23% worldwide similarly. 

In this age of data migrations, it is important to understand the technicalities behind these migrations so that they can be properly implemented.

In this article, we’ll take a closer look at the methods you can use to set up a DynamoDB PostgreSQL connection. Before moving forward, let’s get an overview of DynamoDB and PostgreSQL databases.

What is DynamoDB?

Amazon DynamoDB is a fully managed NoSQL database service offered by AWS (Amazon Web Services). It is designed to provide fast and predictable performance with seamless scalability, making it suitable for applications that require low-latency data access.

Key Features of DynamoDB:

1. Fully Managed: AWS handles operational tasks like hardware provisioning, setup, configuration, and scaling, allowing developers to focus on their applications.
2. Performance at Scale: DynamoDB can handle high traffic loads, supporting millions of requests per second and scaling seamlessly to accommodate varying workloads.
3. Flexible Data Model: Supports both document and key-value store data models, allowing for complex data structures and easy integration with various application architectures.
4. Global Tables: Offers multi-region, fully replicated tables for high availability and low-latency access to data across different geographical locations.

What is PostgreSQL?

PostgreSQL is an open-source, general-purpose, object-relational database management system, or ORDBMS. It is widely used and provides advanced features along with standard compliance. Some of these features include complex queries, foreign keys, triggers, and views—all supporting transactional integrity with full ACID compliance. Inherent in it is vast extensibility for custom data types, functions, and operators.

Key Features of PostgreSQL

• Provides built-in support for JSON, XML, arrays, hstore, and custom types, making it ideal for modern applications that require complex data models.
• PostgreSQL is released under the PostgreSQL License (similar to MIT), which makes it free to use, modify, and distribute.
• Supports Atomicity, Consistency, Isolation, and Durability (ACID), ensuring reliable transactions and data integrity.

How to Set Up DynamoDB PostgreSQL Migration?

The mass popularity of NoSQL databases has also resulted in them being employed in all told use cases without understanding the suitability for the employment case. One fundamental rule that’s usually forgotten is that the NoSQL databases are designed around queries.

Initially, the schema evolves to support the requirement for initial business use cases. However, the business use cases evolve and alter in multiple ways, and shortly the new needs for interacting with the database become unwieldy. This is often the elemental problem that folks usually hit with NoSQL databases.

Due to business needs, organizations sometimes have to migrate to SQL databases from NoSQL Databases. Here we are going to migrate data from DynamoDB to PostgreSQL.

Method 1: Migrate DynamoDB PostgreSQL Data using Hevo’s No Code Data Pipeline

You just need to follow 3 Steps to migrate your DynamoDB PostgreSQL data:

Step 1: Configure your DynamoDB Source

Step 2: Configure your PostgreSQL Destination

Step 3: Create your Automated Pipelines to load data from DynamoDB to PostgreSQL.

Read our docs to learn how you can connect your Amazon DynmoDB and PostgreSQL in a few minutes.

Try Hevo to easily load your DynamoDB data to PostgreSQL!

Method 2: Using Custom Code to Migrate DynamoDB PostgreSQL Data

Prerequisites:

To successfully migrate your data from DynamoDB to PostgreSQL you need to meet the following requirements:

• We will require Lambda Role with full DynamoDB access.
• Secondly, an AWS Lambda with Python as runtime.
• Lastly, a PostgreSQL Database with all its details.

Steps to Connect:

• Step 1: Create an AWS Lambda with Python as a runtime and choose the lambda role having DynamoDB access. We will use the psycopg2 module to attach to the PostgreSQL database from our Python code. Firstly, we’ll import psycog2, boto3, and OS modules.

The Boto3 module is employed to attach to Amazon services like DynamoDB. OS module is employed to induce the environment variables. The psycopg2 module is directly not available in AWS Lambda, so we want to form a layer or directly import the psycopg2 files within the code.

We will make a connection to our PostgreSQL database. we’ll be requiring the Database endpoint, password, and therefore the Database name for the connection.

Here we’ve stored the username, host, database name, and password within the environment variable as an environment variable for not disclosing the main points. within the ‘Configuration’ tab of Lambda, we’ve got the choice to line the Environment variables.

• Step 2: Now we’ll scan or query DynamoDB and fetch the desired details as per our requirement. As an example, we are querying a table for a specific ‘Email’ and getting the information.

• Step 3: Now, we’ll put this data into our PostgreSQL database. We’ll write the PostgreSQL query and add the variable we must augment our PostgreSQL. Then we are going to execute the query and so commit the connection. The complete code is given below.

import psycopg2 
import boto3 
import os 

client - boto3.client('dynamodb') 
connection = psycopg2.connect(user=os.environ['user'], 
	     password=os.environ['password'], 
	     host=os.environ['host'], 
	     database=os.enviroWdatabase'D 
cursor = connection.cursor() 

def lambda_handler(event, context): 
	dynamoQuery = client.query(TableName="user",
				 KeyConditionExpression ="Email = :email", 						ExpressionAttributeValues = {":email": { 'S.: 'test@email.com' })) 
email = dynamoQuery['Items'][0]['email']['S'] postgres_insert_query = """ INSERT INTO users(email) VALUES (%s) """ 
record_to_insert = (email,) 
cursor.execute(postgres_insert_query, r.acord_to_insert) 
connection. commit() count = cursor.rowcount 
return (count, "Record inserted successfully into table") 

• Step 4: We have successfully transferred the info from DynamoDB to PostgreSQL. Similarly, if we must migrate the entire table to scan the whole table and in line with the necessity, we will write the PostgreSQL queries and transfer the info.

Use Cases to transfer your DynamoDB data to Postgres

DynamoDB to Postgres migration provides several benefits. Here are a few use cases:

• Advanced Analytics: You can run sophisticated queries and do data analysis on your DynamoDB data using Postgres’ robust data processing features to gain insights that aren’t attainable with DynamoDB alone.
• Data Consolidation: In the event that you use DynamoDB in conjunction with several other sources, syncing to Postgres enables you to centralize your data for a comprehensive understanding of your operations and to establish a change data capture procedure that ensures there are never again any inconsistencies in your data.
• Analyzing Historical Data: DynamoDB’s historical data is limited. Data sync with Postgres enables long-term data storage and longitudinal trend analysis.
• Compliance and Data Security: Strong data security protections are offered by Postgres. Advanced data governance and compliance management are made possible by syncing DynamoDB data to Postgres, which also guarantees data security.
• Scalability: Postgres is an excellent alternative for increasing organizations with growing DynamoDB data since it can manage massive amounts of data without compromising speed.
• Machine Learning and Data Science: You may use machine learning models for your data for predictive analytics, consumer segmentation, and other purposes if you have DynamoDB data in Postgres.
• Reporting & Visualisation: Although Postgres can be connected to using DynamoDB, Tableau, PowerBI, and Looker (Google Data Studio) are examples of data visualization programs that can connect to Postgres and offer more sophisticated business intelligence capabilities. 

Conclusion

Migrating from DynamoDB to PostgreSQL  offers organizations significant advantages, including cost savings and enhanced flexibility in data management. However, performing this migration could seem like a daunting task without proper tools and skills. 

Hevo simplifies this migration process with its automated, no-code solution, which efficiently manages data integration, schema mapping, and real-time synchronization. By leveraging Hevo, businesses can achieve a smooth and seamless migration, minimizing disruption and allowing them to focus on their core operations. Sign up for Hevo’s 14-day free trial and experience seamless data migration

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