Migration of Database from Amazon DynamoDB to PostgreSQL

January 4, 2022 | Comments(1) |

On the journey to accelerate the modernization process, organizations migrate from on-premises databases and analytics solutions to the cloud.  According to the latest forecast by Gartner Inc, the year 2021 has seen a growth of 23% worldwide, the end-user spending on the public cloud with a total of $332.3 billion, a jump from $270 billion in 2020.

With migration on the rise, database migration involves various intricate details that only technically sound individuals can understand and implement. So let us dive deep into the migration of databases from DynamoDB to PostgreSQL.

Here is a brief about Database, DynamoDB, and PostgreSQL for beginners.

1. What is a Database?

Databases are organized information that can be easily accessed, managed, and developed. Databases are significant to your business/organization because they link to information related to your transaction, product list, customer profiles, and marketing activities. Unless you have one place to store all this information, you never know what is happening inside your business. Without knowing the exact details of your business, business owners make guesses, and guesses are often based on opinions rather than facts.

2. Commonly used database types:

Relational Database:

A relational database stores and organizes data points related to one another. Based on the relational database model, a relational database presents data sets as a collection of tables and provides relational operators to manipulate the data in tabular form.

Relational databases maintain data in tables, providing an efficient, intuitive, and flexible way to store and access structured information. Tables, also known as relations, consist of columns containing one or more data categories, and rows, also known as table records, containing a set of data defined by the category. Applications access data by specifying queries.

Examples of Relational databases are MySQL Database, PostgreSQL, Oracle, MS SQL Server, Sybase, etc.

Non-Relational Database:

A non-relational database is a database that does not incorporate the table/key model that relational database management systems (RDBMS) promote. These databases require data manipulation techniques and processes designed to provide solutions to big data problems. The most popular emerging non-relational database is called NoSQL.

Examples of Relational databases are DynamoDB, MongoDB, Apache Cassandra, Redis, Couchbase, and Apache HBase.

3. What is Dynamo DB, and what are its Limitations?

Amazon DynamoDB is a fully managed NoSQL database service that allows the creation of database tables that can store and retrieve any amount of data. It automatically manages the data traffic of tables over multiple servers and maintains performance. It also relieves the customers from the burden of operating and scaling a distributed database. Hence, hardware provisioning, setup, configuration, replication, software patching, cluster scaling are managed by Amazon.

Limitations of DynamoDB:

  • Deployable only on AWS and cannot be installed on individual desktops/servers
  • Queries – Querying data is extremely limited
  • Table Joins – Joins are impossible
  • No Triggers
  • No foreign keys concept to refer to other table items
  • No server-side scripts

4. Migration of Data from DynamoDB to PostgreSQL:

The mass popularity of NoSQL databases has also resulted in them being used in all use cases without understanding the suitability for the use case. One fundamental rule that is usually forgotten is that the NoSQL databases are designed around queries. Initially, the schema is evolved based on the need for initial business use cases. However, the business use cases evolve and change in multiple ways, and soon the new needs of interacting with the database become unwieldy. This is the fundamental problem that people usually hit with NoSQL databases.

Due to business needs, sometimes organizations feel to migrate to SQL databases from NoSQL Databases. Here we will discuss migrating the DynamoDB data to PostgreSQL.

Requirements to Migrate the DynamoDB data to PostgreSQL:

  1. Lambda Role having DynamoDB full access
  2. AWS Lambda with Python as runtime
  3. PostgreSQL Database with all its details.

5. Step-by-Step Guide:

  1. Create an AWS Lambda with python as a runtime and select the lambda role having DynamoDB access. We will be using psycopg2 module to connect to PostgreSQL database from our python code. Firstly, we will import psycog2, boto3 and OS module. Boto3 module is used to connect to Amazon services like DynamoDB. OS module is used to get the environment variables. Psycopg2 module is directly not available in AWS Lambda, so we need to create a layer or directly import the psycopg2 files in the code. DynamoDB
    We will make a connection to our PostgreSQL database. We will be requiring the Database endpoint, password, and the Database name for the connectionHere we have stored the username, host, database name, and password in the environment variable as an environment variable for not disclosing the details. In the ‘Configuration’ tab of Lambda, we have the option to set the Environment variables.
  2. Now we will scan or query or DynamoDB and fetch the required details as per our requirement. For example, we are querying a table for specific ‘Email’ and getting the data.DynamoDB
  3. Now, we will put this data into our PostgreSQL database. We will write the PostgreSQL query and add the variable we must add to our PostgreSQL. Then we will execute the query and then commit the connection. DynamoDB
  4. Voila! We have successfully transferred the Data from DynamoDB to PostgreSQL. Similarly, if we must migrate the complete table to scan the entire table and according to the requirement, we can write the PostgreSQL queries and transfer the data.
  5. If we must make other CRUD operations on our PostgreSQL, we can directly write the PostgreSQL queries and get the data.

Conclusion:

Cloud database migration involves data loss, capital risks, budget issues, and many other aspects. During the process, the security posture can be vulnerable and unstable which could lead to major business impact. It is recommended to choose an expert cloud migration service provider to manage your data migration requirements.

CloudThat is Microsoft Gold Partner, AWS Advanced Consulting Partner, and a Google Cloud Partner and has successfully led many migration projects for our esteemed clients. So, get in touch with us for quick results.
Feel free to drop a comment or any queries that you have regarding cloud migration, and we will get back to you quickly. To get started, go through our Expert Advisory page and Managed Services Package that is CloudThat’s offerings.

Learn more about Cloud Migration Methodology and implementation here: 5 Key Cloud Migration Challenges and Their Proven Solutions. 

Feel free to drop a comment or any queries that you have regarding cloud migration, and we will get back to you quickly.


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