There are a various number of PostgreSQL clients including standard Drivers to BI and analytics tools. Among all, PostgreSQL is one of the most popular interfaces for data access.
In the modernization process, organizations are migrating from on-premises databases and analytics solutions to the cloud. 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 that lie behind these data migrations so that those can be properly implemented. So, let us have a deep insight into migrating DynamoDB PostgreSQL Data. You will understand various methods to migrate your data. Before moving forward, let’s get an overview of DynamoDB and PostgreSQL databases.
What are Databases?
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A Database is a logically ordered collection of structured data kept electronically in a computer system. A Database Management System (DBMS) is a set of applications that allow users to access databases, alter data, report on data, and visualize data. It also aids in the control of database access.
You need a consolidated place to see all data to get an idea of where the business is going. This data-driven approach is needed to make well-informed decisions rather than just making guesses. Some of the frequently used databases are mentioned below:
1. Relational Database
Tables with rows and columns make up a relational database. It’s a form of database that keeps track of and gives users access to data points that are connected.
A Relational Database is a collection of data elements that are linked together by pre-defined relationships. These elements are laid down in a tabular format with columns and rows. Tables store data about the things that will be represented in the database. A field keeps the actual value of an attribute, while each column in a table carries a specific type of data.
The table’s rows indicate a group of linked values for a single item or entity. A primary key is a unique identifier assigned to each row in a table, while foreign keys are used to link rows from other tables. Without restructuring the database tables, this data may be accessed in a variety of ways.
Examples of Relational databases are Oracle, PostgreSQL, MS SQL Server, MySQL, etc.
2. Non-Relational Database
A Non-Relational Database is one that does not employ the standard tabular schema of rows and columns seen in most database systems. Non-relational databases utilize a storage model that is tailored to the individual needs of the data being stored.
Examples of Non-Relational databases are DynamoDB, MongoDB, Apache Cassandra, Redis, Couchbase, and Apache HBase.
What is DynamoDB?
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Amazon DynamoDB is a fully managed NoSQL database service that enables you to create information base tables that can store and retrieve any data. It automatically manages the information traffic of tables over multiple servers and maintains performance. It also relieves the purchasers from the burden of operating and scaling a distributed database. Hence, hardware provisioning, setup, configuration, replication, software patching, and cluster scaling are managed by Amazon.
However some limitations of DynamoDB include no server-side scripts, table Joins are impossible, no foreign keys concept to talk to other table items, no Triggers, querying data is extremely limited, deployable only on AWS, and can’t be installed on individual desktops/servers.
What is PostgreSQL?
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PostgreSQL is a highly efficient Relational Database Management System (DBMS) that has been developed by the open-source community for more than two decades. PostgreSQL is the principal database for many web services, as well as mobile and analytics apps. SQL (relational) and JSON (non-relational) queries are both supported. On all operating systems, PostgreSQL is well-supported.
You can explore more key features and other details of PostgreSQL here.
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 discuss migrating the DynamoDB data to PostgreSQL.
Method 1: Migrate DynamoDB PostgreSQL Data using Hevo’s No Code Data Pipeline
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Hevo provides an Automated No Code Data Pipeline that helps you move your DynamoDB data swiftly to your 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.
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 can entrust us with your data transfer process by both ETL and ELT processes to a data warehouse, Reverse ETL processes to CRMS, etc and enjoy a hassle-free experience.
You just need to follow 3 Steps to migrate your DynamoDB PostgreSQL data:
Step 1: Configure your DynamoDB Source
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Step 2: Configure your PostgreSQL Destination
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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.
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.
Conclusion
In this article, you gained a basic understanding of databases. You also learned about PostgreSQL and DynamoDB. In addition, 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!
Hevo Data is a No-Code Data Pipeline that offers a faster way to move data from 100+ Data Sources such as DynamoDB, PostgreSQL, and other 40+ Free Sources, into your Data Warehouse. Hevo is fully automated and hence does not require you to code.
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Share your experience with DynamoDB PostgreSQL Migration in the comments section below!