Why I’m Writing This
Last month one of our core production tables hit 2.3TB. P99 query latency went from 30ms to 4.7 seconds. A single vacuum run took 12 hours and still didn’t finish. Someone in the DBA Slack channel joked our table was “basically cold storage at this point.”
I dug through the official docs and every community post I could find. Here’s the thing — the PostgreSQL docs are correct, but they’re not helpful. They tell you the syntax. They don’t tell you when Range partitioning will burn you, or how to unfuck a bad partition key choice.
This is the guide I wish I had three months ago. It’s everything I learned — including the parts that blew up in my face.
Step 1: Do You Actually Need Partitioning?
Don’t partition for the sake of partitioning. This is the #1 mistake I see.
Someone on r/devops put it well: “I’ve seen people partition 50GB tables thinking it’s a magic performance pill. It’s not.”
My rule of thumb:
- Single table >500GB or >100M rows
- Your queries have natural time or geographic boundaries
- You need to regularly purge old data (e.g., keep last 90 days)
- Your autovacuum is getting slower and slower
If you check 2+ boxes, go for it. Otherwise, don’t.
Step 2: Pick Your Strategy — Range or Hash?
Let me cut through the noise.
| Strategy | Best For | Pros | Cons |
|---|---|---|---|
| Range | Time-series, logs, orders | Great query locality, easy old data cleanup | Hotspot on latest partition |
| List | Geographic regions, enum status values | Controlled data distribution | Poor scalability, need rebuild to add values |
| Hash | Even write distribution, avoiding hotspots | Balanced writes, no contention | Terrible for range queries, partition pruning fails on JOINs |
My take: 80% of use cases should use Range with a timestamp key. For the other 20% — high-write-volume systems where you need uniform distribution — Hash is your friend.
Step 3: 2026 Syntax — What Actually Works
PostgreSQL 16+ native partitioning is mature. If you’re still using the old inheritance-based approach, stop. The Reddit threads on that topic are brutal.
Creating a Partitioned Table
-- Parent table
CREATE TABLE orders (
id BIGSERIAL,
created_at TIMESTAMPTZ NOT NULL,
user_id BIGINT NOT NULL,
amount NUMERIC(10,2),
status VARCHAR(20)
) PARTITION BY RANGE (created_at);
-- Partitions
CREATE TABLE orders_2026_q1 PARTITION OF orders
FOR VALUES FROM ('2026-01-01') TO ('2026-04-01');
CREATE TABLE orders_2026_q2 PARTITION OF orders
FOR VALUES FROM ('2026-04-01') TO ('2026-07-01');
-- Indexes on parent table apply to all partitions automatically
CREATE INDEX idx_orders_user_id ON orders (user_id);
CREATE INDEX idx_orders_status ON orders (status);
Auto-Partitioning with pg_partman
Manual partition creation is a fool’s game in 2026.
CREATE EXTENSION pg_partman;
SELECT partman.create_parent(
p_parent_table := 'public.orders',
p_control := 'created_at',
p_type := 'native',
p_interval := '1 month',
p_premake := 3
);
UPDATE partman.part_config
SET infinite_time_partitions = true,
retention = '3 months',
retention_keep_table = false
WHERE parent_table = 'public.orders';
This extension is worshipped on Reddit for good reason. My only complaint: I didn’t understand p_premake on my first try. Woke up to a 3 AM alarm because partitions weren’t pre-created.
Step 4: Partition Pruning — The Make-or-Break
If your queries don’t prune, you’ve gained nothing.
-- Good: prunes to single partition
EXPLAIN ANALYZE
SELECT * FROM orders
WHERE created_at >= '2026-06-01' AND created_at < '2026-07-01';
-- Bad: scans ALL partitions
EXPLAIN ANALYZE
SELECT * FROM orders
WHERE user_id = 12345;
The fix for the bad query? Sub-partition by user_id hash.
CREATE TABLE orders_2026_q2 PARTITION OF orders
FOR VALUES FROM ('2026-04-01') TO ('2026-07-01')
PARTITION BY HASH (user_id);
CREATE TABLE orders_2026_q2_h0 PARTITION OF orders_2026_q2
FOR VALUES WITH (MODULUS 4, REMAINDER 0);
-- Create h1, h2, h3
Now queries filtering by user_id also prune. This saved our ass.
Step 5: Operations and Monitoring
Check Partition Sizes
SELECT
parent.relname AS parent_table,
child.relname AS partition_name,
pg_size_pretty(pg_total_relation_size(child.oid)) AS size
FROM pg_inherits
JOIN pg_class parent ON pg_inherits.inhparent = parent.oid
JOIN pg_class child ON pg_inherits.inhrelid = child.oid
WHERE parent.relname = 'orders'
ORDER BY child.relname;
Automated Maintenance
#!/bin/bash
# Runs daily at 2 AM
psql -d mydb -c "CALL partman.partition_data_proc('public.orders', p_interval := '1 month', p_source_table := 'public.orders_old');"
psql -d mydb -c "DELETE FROM public.orders WHERE created_at < NOW() - INTERVAL '90 days';"
FAQ
Can I change the partition key after creation?
No. Once set, it’s immutable. You’d need to rebuild the entire table. Choose carefully.
Will adding new partitions cause downtime?
No. Adding a partition is a DDL operation, but PostgreSQL 16+ supports CREATE TABLE IF NOT EXISTS — no table locks.
Do foreign keys work with partitioned tables?
Yes, but with a catch: the foreign key must include the partition key. It’s a frustrating limitation.
How do I migrate existing data to a partitioned table?
Use pg_dump to export, create the partitioned table, then import. Or use INSERT INTO ... SELECT in batches. There’s no in-place conversion.
Summary
Partitioning isn’t a silver bullet. But when you get it right — right strategy, right key, automated maintenance — the performance gains are real. We saw 10-20x improvements on our worst queries.
Three rules:
- Pick the right strategy (Range for most cases)
- Make sure your queries actually prune partitions
- Automate everything with pg_partman
Don’t wait until your table explodes. We learned that one the hard way.
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## References & Community Insights
The following authoritative resources were referenced for architectural best practices and specifications:
- [PostgreSQL Official Documentation](https://www.postgresql.org/docs/)
- [Stack Overflow Engineering Blog](https://stackoverflow.blog/engineering/)
- [Redis Enterprise Architecture](https://redis.com/redis-enterprise/)