What is a relational database?
A relational database is a type of database that stores and provides access to data points that are related to one another. Relational databases are based on the relational model, an intuitive, straightforward way of representing data in tables. In a relational database, each row in the table is a record with a unique field called the primary key as the primary identifier of the record. The primary key is used in other tables to refer to the record. This is called a foreign key. The columns of the table hold attributes of the data, and each record usually has a value for each attribute, making it easy to establish the relationships among data points.
What is a 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. Instead, non-relational databases use a storage model that is optimized for the specific requirements of the type of data being stored.
Why Migrate from NoSQL to SQL?
Migrating from a NoSQL database to an SQL database is often driven by changing project requirements and data complexity. SQL databases offer several advantages:
Structured Data: SQL databases enforce a structured schema, which can be helpful for system design where there are complex relationships between data entities.
ACID Compliance: SQL databases provide ACID (Atomicity, Consistency, Isolation, Durability), ensuring data integrity and consistency.
Advanced Querying: SQL databases offer powerful querying capabilities, making it easier to perform complex joins, aggregations, and ad-hoc queries.
Data Integrity: SQL databases support foreign key constraints, unique constraints, and other features that help maintain data integrity.
Key Differences Between NoSQL and SQL Databases
NoSQL and SQL databases have distinct characteristics:
Data Model: NoSQL databases are schema-less and are typically used for unstructured or semi-structured data. SQL databases enforce a structured schema with tables and relations.
Scaling: NoSQL databases are horizontally scalable, making them suitable for high-write, high-read workloads. SQL databases are vertically scalable, which may require more significant hardware upgrades.
Query Language: NoSQL databases often use document-based query languages, while SQL databases use SQL.
Data Schema Design
The first step in migrating from a NoSQL database to an SQL database is to design the data schema. The schema should be designed to support the application.
Once the schema is designed, the data can be migrated from the NoSQL database to the SQL database. The migration process will vary depending on the database and the data model. In general, the migration process involves the following steps:
- Export the data from the NoSQL database. Take a full backup of the database and export the data to a file.
- Transform the data into the SQL schema. You might need to perform some data cleaning and transformation to ensure that the data is in the correct format.
- Import the data into the SQL database. You can use the SQL database’s import tools to import the data.
- Validate the data. Ensure that the data is imported correctly and it works fine with your new system.
Adjusting Models and Schemas
You will need to update your Django models and database schemas to match the SQL data structure. Ensure that your models and migrations reflect the changes made to the PostgreSQL database.
You can use the Django ORM to write new queries that work with your new SQL database. SQL databases offer powerful querying capabilities, making it easier to perform complex joins, aggregations, and ad-hoc queries.
Consider rebuilding indexes on SQL tables to optimize query performance. Identify the fields frequently used in queries, or were indexed in the NoSQL database, and create indexes on those fields.
Migrating from a NoSQL database to an SQL database can be a challenging process. However, the benefits of SQL databases, such as structured data, ACID compliance, and advanced querying, can make the migration worthwhile.