How to Handle Large PostgreSQL Schemas with a GUI Tool

Postgresql • 09-Sep-2025

by Roxana Haidiner

Handle Massive Databases

Design even with 10,000+ tables.

At first, a database looks simple. A few tables, some relationships, and you know where everything is.

But when the schema grows to hundreds or even thousands of tables, things get difficult:

Finding tables takes time,
Making changes feels risky,
And keeping different environments in sync is hard.

This is where a visual tool like DbSchema helps.

Everything you do in DbSchema is stored in a design model (.dbs file) that you can reopen anytime or share with your team. Read more about the design model →

Here’s what you really need from a tool when working with a very large PostgreSQL schema, and how DbSchema provides it:

1. Clarity: See the Schema Visually

Split thousands of tables into smaller, focused diagrams.
Search by table or column name and jump straight to it.
Use colors, groups, and notes to highlight areas like HR, Orders, or Inventory.

This makes the schema understandable again, even with more than 10,000 tables.

Create Multiple Diagrams

2. Control: Make Safe Changes

Edit tables visually in the diagram (add columns, change datatypes).
Use Schema Compare to check differences between your model and the live database.
Generate migration scripts automatically, so you don’t miss anything.

Example migration:

ALTER TABLE company.orders
ADD COLUMN discount NUMERIC(5,2);

This gives you confidence that changes won’t break production.

Exists in the project

Missing in Postgres Database

3. Environment Management: Keep Dev, Stage, and Prod in Sync

Save multiple connections inside the same project.
Switch between them with one click.
Apply the same schema updates across all environments consistently.

Example:

company_dev
company_stage
company_prod

This saves you from human errors and keeps all teams aligned.

4. Documentation: Share Knowledge Easily

DbSchema can generate HTML5 documentation that is:

Complete - includes tables, columns, indexes, and foreign keys
Visual - shows diagrams for better understanding
Interactive - click and navigate between tables
Searchable - find any table or column by name
Shareable - publish it on an internal site

This stops everyone from asking you where things are and makes onboarding easier.

5. Data Tools: Work With the Schema, Not Just See It

Use the Visual Query Builder for joins without memorizing columns.
Explore data with the Relational Data Explorer to see how rows link across tables.
Generate realistic test data (100k+ rows) to check performance before deploying changes.

This way, you can actually use the schema, not just look at it.

5. Automation Scripts

With Automation Scripts in Groovy, you can:

create monthly partitions,
export schema snapshots,
check for missing indexes,
or clean up old data.

In DbSchema you can write Automation Scripts in Groovy. They run directly from the project, so you don’t have to manage external tools.

Example: create next month’s partition automatically


def nextMonth = java.time.LocalDate.now().plusMonths(1)
def start = nextMonth.withDayOfMonth(1)
def end   = start.plusMonths(1)

def sql = """
CREATE TABLE company.transactions_${start.getYear()}_${String.format("%02d", start.getMonthValue())}
PARTITION OF company.transactions
FOR VALUES FROM ('${start}') TO ('${end}');
"""

db.execute(sql)
println "Partition for ${start.getMonth()} ${start.getYear()} created."