How to Handle Large PostgreSQL Schemas with a GUI Tool

Handle Massive Databases

Design even with 10,000+ tables.

When a database is small, everything looks simple. You open the diagram, see a few tables, and it all makes sense.

At first a database looks simple. But as projects grow, so do the tables. Soon the schema feels heavy, and even small changes become hard to track.

This is where DbSchema makes the work easier.

1. Organize With Multiple Diagrams

DbSchema lets you split a big schema into smaller diagrams. For example:

• one diagram for Orders & Transactions,
• another for Customers & Billing,
• one more for HR.

The database is the same, but you look only at the part you need. This keeps things clear even if the schema has more than 10,000 tables.

Create Multiple Diagrams

2. Connect to Multiple Databases

Most projects don’t have only one database. You usually work with Dev, Stage, and Prod.

In DbSchema you can save all connections in the same project and switch between them easily.

Example:

company_dev
company_stage
company_prod

One click, and you are connected to the right place. No need to remember passwords or JDBC URLs each time.

3. Make Safe Changes

Changing a big schema is stressful. Instead of running ALTER TABLE directly in production, do it step by step:

• Change the table visually in the diagram.
• Use Schema Compare to see what changed between the model and the database.
• Let DbSchema generate a migration script.

Example migration:

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

Review it, test in Dev, then apply in Prod. This makes changes predictable and safe.

Exists in the project

Missing in PostgreSQL Database

4. Documentation Everyone Can Read

Large schemas confuse not only developers, but also analysts and new colleagues. DbSchema can generate HTML5 documentation that is:

• Complete - includes tables, columns, indexes, and foreign keys
• Visual - shows diagrams for better understanding
• Interactive - you can click and navigate between tables
• Searchable - quickly find a column or table by name
• Shareable - publish it on an internal site for the whole team

This way everyone can explore the schema without asking you each time.

5. Automation Scripts

Large databases often need repetitive tasks:

• creating new partitions every month,
• checking if important indexes exist,
• exporting schema snapshots for backups,
• or cleaning 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."

With scripts like this you can:

• keep partitions up to date,

• schedule routine checks,

• or generate data exports with a single click.

Wrap-Up

Large PostgreSQL databases are not easy to handle. But with DbSchema you can:

• split diagrams into smaller views,
• work with multiple environments,
• apply changes safely,
• generate documentation,
• and automate routine tasks.

This workflow keeps the database clear and manageable, even when it grows beyond 10,000 tables.

Try it yourself for free with DbSchema. Download here.