DynamoDB PostgreSQL Migration: 2 Easy Methods

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.

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
• Method 2: Using Custom Code to Migrate DynamoDB PostgreSQL Data

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

Hevo provides an Automated No Code Data Pipeline that helps you swiftly migrate DynamoDB to PostgreSQL. You can set up a Data Warehouse managed by Hevo on the fly, as part of the Integration process. The ingested data from the source is first stored in a Data Warehouse managed by Hevo and then loaded to the destination, such as Databases, or Business Applications.

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Hevo’s fault-tolerant architecture will enrich and transform your data in a secure and consistent manner and load it to your destination without any assistance from your side.

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.

Here are more reasons to try Hevo:

• Smooth Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to your schema in the desired Data Warehouse.
• Exceptional Data Transformations: Best-in-class & Native Support for Complex Data Transformation at fingertips. Code & No-code Fexibilty designed for everyone.
• Quick Setup: Hevo with its automated features, can be set up in minimal time. Moreover, with its simple and interactive UI, it is extremely easy for new customers to work on and perform operations.
• Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
• Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.

Try Hevo to easily load your DynamoDB data to PostgreSQL!

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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.

• 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

In this article, you learned 2 different methods to migrate your data from DynamoDB to PostgreSQL easily.

However, migrating complex data from a diverse set of data sources like DynamoDB, other Databases, CRMs, Project management Tools, Streaming Services, and Marketing Platforms to your PostgreSQL Database can seem to be quite challenging. This is where a simpler alternative like Hevo can save your day!

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Share your experience with DynamoDB PostgreSQL Migration in the comments section below!