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description=Drizzle ORM is a lightweight and performant TypeScript ORM with developer experience in mind.;

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ns migrations overview generate migrate push pull export check up studio custom migrations migrations for teams web and mobile drizzle config ts seeding overview generators versioning access your data query select insert update delete filters utils joins aliases magic sql operator sql comments performance queries serverless advanced set operations generated columns transactions batch cache dynamic query building read replicas custom types codecs jit mappers goodies validations zod valibot typebox arktype typebox legacy effect schema extensions eslint plugin drizzle graphql system light dark become a sponsor twitter discord v1 0 98 benchmarks extension studio studio package gateway drizzle run our goodies our primary backer our cloud partner drizzle is giving you 10 off turso scaler and pro for 1 year product by drizzle team one dollar stats 1 per mo web analytics christmas deal drizzle relations fundamentals in the world of databases especially relational databases the concept of relations is absolutely fundamental think of relations as the connections and links between different pieces of data just like in real life where people have relationships with each other or objects are related to categories databases use relations to model how different types of information are connected and work together normalization normalization is the process of organizing data in your database to reduce redundancy duplication and improve data integrity accuracy and consistency think of it like tidying up a messy filing cabinet instead of having all sorts of papers crammed into one folder you organize them into logical folders and categories to make everything easier to find and manage why is normalization important reduces data redundancy imagine storing a customer s address every time they place an order if the address changes you d have to update it in multiple places normalization helps you store information in one place and refer to it from other places minimizing repetition improves data integrity less redundancy means less chance of inconsistencies if you update an address in one place it s updated everywhere it s needed prevents anomalies normalization helps prevent issues like insertion anomalies difficulty adding new data because you re missing related information update anomalies having to update the same information in multiple rows deletion anomalies accidentally losing valuable information when you delete something seemingly unrelated easier to understand and maintain a normalized database is generally more logically structured and easier to understand query and modify normalization is often described in terms of normal forms 1nf 2nf 3nf and beyond while the details can get quite technical the core ideas are straightforward 1nf first normal form atomic values goal each column should hold a single indivisible value no repeating groups of data within a single cell example instead of having a single address column that stores 123 main st city usa you d break it down into separate columns street_address city state zip_code unnormalized violates 1nf create table customers_unnormalized customer_id integer primary key name varchar 255 address varchar 255 problem multiple pieces of info in one column normalized to 1nf create table customers_1nf customer_id integer primary key name varchar 255 street_address varchar 255 city varchar 255 state varchar 255 zip_code varchar 10 2nf second normal form eliminate redundant data dependent on part of the key goal applies when you have a table with a composite primary key a primary key made up of two or more columns 2nf ensures that all non key attributes are fully dependent on the entire composite primary key not just part of it imagine we have a table called order_items this table tracks items within orders and we use a composite primary key order_id product_id because a single order can have multiple of the same product though in this simplified example let s assume each product appears only once per order for clarity but the composite key logic still applies expand for visual example create table orderitems_unnormalized order_id integer product_id varchar 10 product_name varchar 100 product_price decimal 10 2 quantity integer order_date date primary key order_id product_id composite primary key insert into orderitems_unnormalized order_id product_id product_name product_price quantity order_date values 101 a123 laptop 1200 00 1 2023 10 27 101 b456 mouse 25 00 2 2023 10 27 102 a123 laptop 1200 00 1 2023 10 28 103 c789 keyboard 75 00 1 2023 10 29 orderitems_unnormalized pk order_id product_id product_name product_price quantity order_date 101 a123 laptop 1200 00 1 2023 10 27 101 b456 mouse 25 00 2 2023 10 27 102 a123 laptop 1200 00 1 2023 10 28 103 c789 keyboard 75 00 1 2023 10 29 problem notice that product_name and product_price are repeated whenever the same product_id appears in different orders these attributes are only dependent on product_id which is part of the composite primary key order_id product_id but not the entire key this is a partial dependency to achieve 2nf we need to remove the partially dependent attributes product_name product_price and place them in a separate table where they are fully dependent on the primary key of that new table normalization to 2nf visual explanation 1 m products orderitems_2nf pk product_id pk order_id product_id product_name quantity product_price order_date fk product_id create table products product_id varchar 10 primary key product_name varchar 100 product_price decimal 10 2 create table orderitems_2nf order_id integer product_id varchar 10 quantity integer order_date date primary key order_id product_id composite primary key remains foreign key product_id references products product_id foreign key to products insert data into products insert into products product_id product_name product_price values a123 laptop 1200 00 b456 mouse 25 00 c789 keyboard 75 00 insert data into orderitems_2nf referencing products insert into orderitems_2nf order_id product_id quantity order_date values 101 a123 1 2023 10 27 101 b456 2 2023 10 27 102 a123 1 2023 10 28 103 c789 1 2023 10 29 3nf third normal form eliminate redundant data dependent on non key attributes goal remove data that is dependent on other non key attributes this is about eliminating transitive dependencies problem let s say we have a suppliers table we store supplier information including their zip_code city and state supplier_id is the primary key create table suppliers supplier_id varchar 10 primary key supplier_name varchar 255 zip_code varchar 10 city varchar 100 state varchar 50 insert into suppliers supplier_id supplier_name zip_code city state values s1 acme corp 12345 anytown ny s2 beta inc 67890 otherville ca s3 gamma ltd 12345 anytown ny suppliers pk supplier_id supplier_name zip_code city state s1 acme corp 12345 anytown ny s2 beta inc 67890 otherville ca s3 gamma ltd 12345 anytown ny solution to achieve 3nf we remove the attributes dependent on the non key attribute city state dependent on zip_code and put them into a separate table keyed by the non key attribute itself zip_code normalization to 3nf visual explanation 1 m zip_codes suppliers pk zip_code pk supplier_id city supplier_name state fk zip_code create table zip_codes zip_code varchar 10 primary key city varchar 100 state varchar 50 create table suppliers supplier_id varchar 10 primary key supplier_name varchar 255 zip_code varchar 10 foreign key to zip_codes foreign key zip_code references zip_codes zip_code insert data into zip_codes insert into zip_codes zip_code city state values 12345 anytown ny 67890 otherville ca insert data into suppliers referencing zip_codes insert into suppliers supplier_id supplier_name zip_code values s1 acme corp 12345 s2 beta inc 67890 s3 gamma ltd 12345 good to know there are additional normal forms such as 4nf 5nf 6nf eknf etnf and dknf we won t cover these here but we will create a dedicated set of tutorials for them in our guides and tutorials section database relationships one to one in a one to one relationship each record in table a is related to at most one record in table b and each record in table b is related to at most one record in table a it s a very direct exclusive pairing use cases examples user profiles and user account details think of a website each user account in a users table might have exactly one user profile in a userprofiles table containing more detailed information employees and parking spaces an employees table and a parkingspaces table each employee might be assigned at most one parking space and each parking space is assigned to at most one employee splitting tables for organization sometimes you might split a very wide table into two for better organization or security reasons maintaining a 1 1 relationship between them table a one side table b one side pk a fk a foreign key referencing table a one to many in a one to many relationship one record in table a can be related to many records in table b but each record in table b is related to at most one record in table a think of it as a parent child relationship use cases examples customers and orders one customer can place many orders but each order belongs to only one customer authors and books one author can write many books but let s simplify for now and say each book is written by one primary author departments and employees one department can have many employees but each employee belongs to only one department table a one side table b many side pk a fk a foreign key referencing table a one many many to many in a many to many relationship one record in table a can be related to many records in table b and one record in table b can be related to many records in table a it s a more complex bidirectional relationship use cases examples students and courses one student can enroll in many courses and one course can have many students enrolled products and categories one product can belong to multiple categories e g a t shirt can be in clothing and summer wear categories and one category can contain many products authors and books a book can be written by multiple authors and an author can write multiple books table a many side junction table table b many side pk a fk a fk b fk b many junction many many to many relationships are not directly implemented with foreign keys between the two main tables instead you need a junction table also called an associative table or bridging table this table acts as an intermediary to link records from both tables table for students many side create table students id integer primary key name varchar 255 table for courses many side create table courses id integer primary key name varchar 255 credits integer junction table enrollments connects students and courses m m relationship create table enrollments id integer generated always as identity primary key optional but good practice for junction tables student_id integer course_id integer enrollment_date date composite foreign keys often part of a composite primary key or unique constraint foreign key student_id references students id foreign key course_id references courses id unique student_id course_id prevent duplicate enrollments for the same student and course why foreign keys you might think of foreign key constraints as simply a way to validate data ensuring that when you enter a value in a foreign key column that value actually exists in the primary key column of another table and you d be partially right this value checking is the mechanism foreign keys use but it s crucial to understand that this validation is not the end goal it s the means to a much larger purpose foreign key constraints are fundamentally about 1 explicitly defining and enforcing relationships we ve discussed relationships like one to many between customers and orders a foreign key is the sql language s way of telling the database hey database i want to enforce a 1 m relationship here every value in the customer_id column of the orders table must correspond to a valid customer_id in the customers table it s not just a suggestion it s a constraint the database actively enforces the database becomes relationship aware because of the foreign key 2 maintaining referential integrity this is the core of data integrity in the context of relationships referential integrity means that relationships between tables remain consistent and valid over time foreign keys prevent orphaned records what s an orphaned record in our customer order example an order that exists in the orders table but doesn t have a corresponding customer in the customers table would be an orphan foreign keys prevent this from happening or control what happens if you try to delete a customer with orders via cascade set null etc why is preventing orphans important orphaned records break the logical structure of your data if you have an order without a customer you lose crucial context queries become unreliable reports become inaccurate and your application s logic can break down example without a foreign key you could accidentally delete a customer from the customers table while their orders still exist in the orders table suddenly you have orders that point to a customer that no longer exists a foreign key constraint prevents this data inconsistency 3 facilitating database design and understanding foreign keys are not just about technical enforcement they are also a crucial part of database design documentation when you see a foreign key in a database schema it immediately tells you table x is related to table y in this way it s a clear visual and structural indicator of relationships this makes databases easier to understand maintain and evolve over time new developers can quickly grasp how different parts of the database are connected in essence foreign key constraints are not just about checking values they are about defining the rules of your data relationships actively enforcing those rules at the database level guaranteeing data integrity and consistency within those relationships making your database more robust reliable and understandable why not foreign keys while highly beneficial there are some scenarios where you might reconsider or use foreign keys with caution these are typically edge cases and often involve trade offs 1 performance overhead in very high write environments scenario extremely high volume transactional systems e g real time logging very high frequency trading platforms massive iot data ingestion explanation every time you insert or update data in a table with a foreign key the database system needs to perform checks to ensure referential integrity in extremely high write scenarios these checks can introduce a small but potentially noticeable performance overhead 2 distributed database systems and cross node foreign keys scenario systems where data is distributed across multiple database nodes or clusters common in sharded databases cloud environments an...