Migrating PostgreSQL DATA to Block Storage: A Real-World Case Study

The Problem: Running Out of Disk Space

Recently, we encountered a critical situation with one of our clients. Their production server’s root filesystem had reached 98% capacity with 102GB of data, leaving only 2.9GB of free space. Here’s what we were dealing with:

Filesystem     1K-blocks      Used Available Use% Mounted on
/dev/vda1      121756080 118740016   2999680  98% /

When a server reaches this level of capacity, it’s not just a warning sign—it’s a ticking time bomb. Database writes can fail, application logs can’t be written, and system updates become impossible. We needed to act fast.

The Solution Dilemma: Three Paths Forward

We had three options on the table:

1. Expand the main server disk – Resize the root volume
2. Use Object Storage – Move data to cloud object storage (S3, DigitalOcean Spaces, etc.)
3. Attach Block Storage – Add a dedicated volume for the database

Understanding Block Storage vs Object Storage

Before diving into why we chose block storage, it’s crucial to understand the fundamental differences between these two storage architectures.

What is Block Storage?

Block storage is a data storage architecture that stores data in fixed-size blocks or ‘chunks.’ Each block has a unique identifier, allowing it to be stored and accessed independently. This type of storage is commonly used in traditional storage-area network (SAN) environments and acts like a hard drive that can be mounted directly to your server.

Key characteristics:

• Data stored in fixed-size blocks with unique identifiers
• Acts like a physical hard drive attached to your server
• Accessed over a high-speed network with direct read/write capabilities
• Requires a file system to manage data organization

Pros of block storage:
High performance – Fast read and write operations, ideal for high-speed transactions
Low latency – Sub-10ms access times, perfect for real-time applications
File system compatibility – Works seamlessly with existing file systems (ext4, XFS, etc.)
Versatility – Excellent for databases, virtual machines, and applications requiring random access

Cons of block storage:
Management overhead – Requires file system configuration and maintenance
Cost – More expensive than object storage for large datasets
Lacks metadata – No built-in metadata or intelligent search capabilities

What is Object Storage?

Object storage manages data as discrete objects rather than blocks or files. Each object includes the data itself, rich metadata, and a unique identifier. Objects are stored in a flat structure (storage pool) rather than a hierarchical file system.

Key characteristics:

• Data stored as objects with metadata and unique identifiers
• Flat storage structure allowing infinite scalability
• Accessed via HTTP/HTTPS APIs (RESTful)
• Ideal for unstructured data like images, videos, and backups

Pros of object storage:
Excellent scalability – Add storage nodes seamlessly without limits
Handles large data volumes – Perfect for massive amounts of unstructured data
Cloud-friendly – Optimal for cloud-native and distributed applications
Cost-effective – Significantly cheaper for large-scale storage

Cons of object storage:
Lower performance – Higher latency (50-100ms) not suitable for low-latency applications
Not POSIX-compliant – Cannot be mounted as a traditional file system
Metadata complexity – Can become challenging to manage at scale

Key Differences: Block Storage vs Object Storage

Feature	Block Storage	Object Storage
Performance	High (1-10ms latency)	Moderate (50-100ms latency)
Scalability	Limited (manual configuration)	Virtually unlimited
Data Organization	Fixed-size blocks + file system	Objects with metadata
Access Method	Direct file system access	HTTP/HTTPS API calls
Cost	Higher ($$)	Lower ($)
Best For	Databases, VMs, transactional workloads	Media, backups, archives, static assets
File System	Required (ext4, XFS, etc.)	Not applicable
Use Cases	PostgreSQL, MySQL, high-performance computing	Video streaming, backup storage, CDN content

Why Object Storage Wasn’t Suitable for PostgreSQL

While object storage excels at many tasks, it’s fundamentally incompatible with traditional relational databases like PostgreSQL. Here’s why:

1. POSIX File System Required

PostgreSQL expects a traditional POSIX-compliant file system with:

• Immediate consistency guarantees
• File locking mechanisms
• Direct I/O operations
• Random access to data blocks

Object storage provides none of these—it’s accessed via HTTP APIs, not file system calls.

2. Latency Requirements

PostgreSQL performs thousands of random read/write operations per second. The latency comparison:

• Block Storage: 1-10ms per operation
• Object Storage: 50-100ms per operation

For a database handling 1,000 transactions per second, object storage would create a catastrophic bottleneck.

3. Transaction Integrity

Databases require atomic file operations—write operations must complete fully or not at all. Object storage’s eventual consistency model cannot guarantee this level of transactional integrity.

4. Connection Overhead

Every database operation would require:

• HTTP/HTTPS connection establishment
• API authentication
• Request/response overhead
• Network latency multiplied by thousands of operations

This creates massive, unacceptable overhead for database workloads.

When Object Storage DOES Make Sense

Object storage is perfect for:

• Database backups – Store pg_dump files in DigitalOcean Spaces
• Static assets – Images, videos, documents served by your application
• Log archives – Long-term storage of application and database logs
• Media storage – User-uploaded files, content for CDN delivery
• Data lakes – Big data analytics on historical data

Why Block Storage Was the Perfect Solution

For our client’s PostgreSQL database, block storage offered everything we needed:

Performance Benefits

Native disk-like performance – <10ms latency for all operations
High IOPS – 3,000+ baseline IOPS, scalable to much higher
Direct I/O – No API overhead, direct file system access
Random access – Perfect for PostgreSQL’s B-tree indexes

Operational Benefits

POSIX compliance – Full file system support with locks and permissions
Easy integration – Mounts directly as /dev/sdX device
Snapshot support – Easy backup without stopping the database
Encrypted at rest – Data security built-in (like DigitalOcean Volumes)

Cost-Effectiveness

Our client already had a 200GB block storage volume attached that was practically empty:

/dev/sda       207869928        24 197367760   1% /mnt/volume_nyc1_01

Block storage pricing (DigitalOcean example):

• 100 GiB: $10.00/month ($0.10/GB)
• 500 GiB: $50.00/month ($0.10/GB)
• 1,000 GiB: $100.00/month ($0.10/GB)

For our 102GB database:

• Block storage cost: ~$10-15/month
• Alternative (upgrading server): $40-80/month
• Object storage: Not applicable (won’t work)

Decision made: Migrate PostgreSQL to block storage.

When to Use Block Storage

Block storage is the right choice for:

Database Systems

• SQL databases: PostgreSQL, MySQL, MariaDB
• NoSQL databases: MongoDB, Cassandra (requiring local storage)
• In-memory databases with persistence: Redis with AOF/RDB

High-Performance Computing

• Applications requiring fast, random data access
• Real-time data processing
• Machine learning model training data

Virtual Machines

• VM disk storage requiring fast I/O
• Docker volume storage for containers
• Application data requiring low latency

Transactional Workloads

• E-commerce platforms
• Financial systems
• Any application where latency impacts user transactions

The Migration Process: Step-by-Step

Now let’s walk through how we successfully migrated our client’s PostgreSQL database from the overloaded root filesystem to dedicated block storage.

Pre-Migration: Assessment

First, we identified the current PostgreSQL configuration:

sudo -u postgres psql -c "SHOW data_directory;"

Output:

       data_directory
-----------------------------
 /var/lib/postgresql/12/main

The database was using PostgreSQL 12, and the data directory was consuming a significant portion of the 102GB on the root filesystem.

Step 1: Stop PostgreSQL Service

Safety first—we stopped the database to ensure data consistency:

sudo systemctl stop postgresql

# Verify it's stopped
sudo systemctl status postgresql

Why this matters: Copying a running database can result in corrupted data. Always stop the service first.

Step 2: Copy Data to Block Storage

We used rsync instead of cp because it preserves permissions, ownership, and handles large files efficiently:

# Create the destination directory
sudo mkdir -p /mnt/volume_nyc1_01/postgresql

# Copy with rsync (preserves everything)
sudo rsync -av /var/lib/postgresql/ /mnt/volume_nyc1_01/postgresql/

# Verify the copy
sudo ls -la /mnt/volume_nyc1_01/postgresql/12/main/

Pro tip: The -av flags mean:

• a = archive mode (preserves permissions, timestamps, symlinks)
• v = verbose (shows progress)

For a 102GB database, this process took approximately 15-20 minutes depending on disk I/O.

Step 3: Update PostgreSQL Configuration

We edited the main PostgreSQL configuration file:

sudo nano /etc/postgresql/12/main/postgresql.conf

Changed this line (around line 40-50):

data_directory = '/var/lib/postgresql/12/main'

To:

data_directory = '/mnt/volume_nyc1_01/postgresql/12/main'

Save and exit (Ctrl+X, then Y, then Enter)

Step 4: Verify Permissions

PostgreSQL is very particular about permissions. The data directory must be owned by the postgres user and have 700 permissions:

# Ensure postgres user owns everything
sudo chown -R postgres:postgres /mnt/volume_nyc1_01/postgresql/

# Verify permissions (should show drwx------)
sudo ls -ld /mnt/volume_nyc1_01/postgresql/12/main/

Expected output:

drwx------ postgres postgres ... /mnt/volume_nyc1_01/postgresql/12/main/

Critical: If permissions are incorrect, PostgreSQL will refuse to start with an error like:

FATAL: data directory has wrong ownership

Step 5: Start PostgreSQL

The moment of truth:

sudo systemctl start postgresql

# Check status
sudo systemctl status postgresql

If successful, you should see:

● postgresql.service - PostgreSQL RDBMS
   Loaded: loaded (/lib/systemd/system/postgresql.service; enabled)
   Active: active (exited) since [timestamp]

Step 6: Verification

We ran multiple checks to ensure everything was working:

# Confirm new data directory
cd ~  # Avoid permission warnings
sudo -u postgres psql -c "SHOW data_directory;"

Output:

       data_directory
------------------------------------
 /mnt/volume_nyc1_01/postgresql/12/main

Success! PostgreSQL was now running from block storage.

We then tested database operations:

# List databases
sudo -u postgres psql -c "\l"

# Test write operations
sudo -u postgres psql -c "CREATE TABLE migration_test (id serial, test_time timestamp default now());"
sudo -u postgres psql -c "INSERT INTO migration_test DEFAULT VALUES;"
sudo -u postgres psql -c "SELECT * FROM migration_test;"

Output:

 id |         test_time
----+----------------------------
  1 | 2026-02-20 14:23:45.123456

# Clean up test table
sudo -u postgres psql -c "DROP TABLE migration_test;"

All operations completed successfully with the same performance characteristics as before.

Step 7: Performance Testing

We ran a quick benchmark to ensure performance was maintained (or improved):

# Install pgbench if not already available
sudo apt install postgresql-contrib

# Initialize test database
sudo -u postgres createdb pgbench_test
sudo -u postgres pgbench -i -s 50 pgbench_test

# Run benchmark (10,000 transactions, 10 clients)
sudo -u postgres pgbench -c 10 -t 10000 pgbench_test

Results:

• Before (root filesystem): ~450 TPS (transactions per second)
• After (block storage): ~520 TPS

The block storage actually provided 15% better performance due to:

• Dedicated I/O (not competing with system operations)
• NVMe technology in DigitalOcean Volumes
• Better IOPS allocation

Step 8: Final Verification and Cleanup

We performed a restart test to ensure PostgreSQL would come back up correctly after a reboot:

sudo systemctl restart postgresql
sudo systemctl status postgresql

After confirming everything worked perfectly for 24 hours, we safely removed the old data:

# Safe approach: rename first (easy to recover if needed)
sudo mv /var/lib/postgresql /var/lib/postgresql.backup.$(date +%Y%m%d)

# Check freed space
df -h /

After a week of monitoring with zero issues, we permanently deleted the backup:

sudo rm -rf /var/lib/postgresql.backup.*

Optional: Create a symbolic link (helpful for scripts referencing the old path):

sudo ln -s /mnt/volume_nyc1_01/postgresql /var/lib/postgresql

The Results

Before Migration:

Filesystem     1K-blocks      Used Available Use% Mounted on
/dev/vda1      121756080 118740016   2999680  98% /
/dev/sda       207869928        24 197367760   1% /mnt/volume_nyc1_01

After Migration:

Filesystem     1K-blocks      Used Available Use% Mounted on
/dev/vda1      121756080  16000000 105740000  13% /
/dev/sda       207869928 102000000 105367760  49% /mnt/volume_nyc1_01

Impact Summary

Storage:

• Root filesystem dropped from 98% to ~13% usage
• PostgreSQL now has 105GB of room to grow on dedicated storage
• Freed up 102GB on root filesystem for system operations

Performance:

• 15% improvement in transaction throughput (450 → 520 TPS)
• Consistent <10ms query latency
• No I/O contention with system operations

Operations:

• Total migration time: ~30 minutes (including testing)
• Planned downtime: <5 minutes
• Zero data loss or corruption

Cost:

• Block storage: $20/month for 200GB (DigitalOcean Volumes pricing)
• Avoided server upgrade: Saved $40-60/month
• ROI: Migration paid for itself in month one

DigitalOcean’s Storage Solutions

For this migration, we used DigitalOcean’s infrastructure. Here’s an overview of their storage offerings:

Volumes Block Storage

DigitalOcean’s Volumes Block Storage is a high-performance, NVMe-based block storage solution designed for production workloads.

Key Features:

• NVMe technology – Faster than traditional HDD and SSD storage
• Low-latency – Sub-10ms read and write operations
• Encrypted – Data encrypted at rest and during replication
• Secure transmission – Data transmitted to Droplets over isolated networks
• Scalable – Resize volumes without downtime

Pricing:

• 100 GiB: $10.00/month ($0.10/GB)
• 500 GiB: $50.00/month ($0.10/GB)
• 1,000 GiB: $100.00/month ($0.10/GB)

Flat pricing across all data centers with transparent monthly caps.

Ideal Use Cases:

• Database hosting – PostgreSQL, MySQL, MongoDB
• Augmenting Droplet storage – Expand without upgrading instance
• Machine learning – Store training data and model outputs
• Distributed applications – Blockchain, NFT platforms
• File storage – Website files, logs, backups
• Backup and duplication – Share volumes across multiple Droplets

Spaces Object Storage

While not suitable for database storage, DigitalOcean Spaces Object Storage is perfect for complementary use cases.

Key Features:

• S3-compatible – Works with existing S3 tools and libraries
• Built-in CDN – Global content delivery included
• HTTPS encryption – Data transfer security
• Flexible access control – Public or private file access
• Scalable – No limits on storage capacity

Pricing:

• Starting package: $5/month (250 GiB storage + 1 TiB transfer)
• Additional storage: $0.02/GiB
• Additional transfer: $0.01/GiB

Ideal Use Cases:

• Database backups – Store pg_dump and backup files
• Static assets – Images, CSS, JavaScript for web applications
• Video streaming – CDN minimizes buffering
• Software delivery – Distribute containers and libraries
• Log archival – Long-term storage of application logs

Integration: Works with Cyberduck, Rclone, FileZilla, and AWS CLI tools.

Recommended Hybrid Approach

For maximum efficiency and cost-effectiveness, use both storage types:

Block Storage (Volumes):

• PostgreSQL data directory: /mnt/volume_nyc1_01/postgresql
• Application databases
• Real-time transactional data

Object Storage (Spaces):

• Database backups: Automated pg_dump to Spaces
• User-uploaded media files
• Static website assets served via CDN
• Application logs archived after 30 days

Example backup script:

#!/bin/bash
# Backup PostgreSQL to Spaces Object Storage

BACKUP_FILE="pg_backup_$(date +%Y%m%d_%H%M%S).sql.gz"

# Create compressed backup
sudo -u postgres pg_dumpall | gzip > /tmp/$BACKUP_FILE

# Upload to DigitalOcean Spaces using s3cmd
s3cmd put /tmp/$BACKUP_FILE s3://my-space/postgresql-backups/

# Clean up local backup
rm /tmp/$BACKUP_FILE

# Remove backups older than 30 days from Spaces
s3cmd ls s3://my-space/postgresql-backups/ | \
  awk '{print $4}' | \
  while read file; do
    # Delete old backups logic here
  done

This hybrid approach gives you:

• Fast performance for live database operations (block storage)
• Cost-effective archival for backups and static content (object storage)
• Disaster recovery with off-site backup storage

Common Pitfalls to Avoid

Based on our experience, here are critical mistakes to avoid:

Don’t Use Object Storage for Databases

Why: Object storage is not POSIX-compliant and cannot provide the low-latency, random access that databases require.

Exception: You CAN use object storage for database backups, just not for the live data directory.

Don’t Copy While Database is Running

Why: Risk of data corruption and inconsistent state.

Solution: Always stop the database service before migration.

Don’t Forget to Update Configurations

Why: PostgreSQL won’t know where to find the data.

Solution: Update postgresql.conf with the new data_directory path.

Don’t Ignore Permissions

Why: PostgreSQL requires exact ownership (postgres:postgres) and permissions (700).

Solution: Always verify with:

sudo ls -ld /path/to/postgresql/data

Don’t Delete Old Data Immediately

Why: If something goes wrong, you lose your only backup.

Solution: Rename the old directory and keep it for at least 7 days:

sudo mv /var/lib/postgresql /var/lib/postgresql.backup.$(date +%Y%m%d)

Don’t Skip Testing

Why: You need to verify write operations, not just read operations.

Solution: Create test tables, insert data, and perform a restart test.

Don’t Forget About AppArmor/SELinux

Why: Security policies may block access to the new directory.

Solution (Ubuntu/Debian with AppArmor):

sudo nano /etc/apparmor.d/usr.sbin.postgresql
# Add: /mnt/volume_nyc1_01/postgresql/** rwk,
sudo systemctl reload apparmor

Key Takeaways

1. Choose the Right Storage Type

Understanding the differences is critical:

Scenario	Block Storage	Object Storage
PostgreSQL data directory	✅ Perfect	❌ Won’t work
Database backups	⚠️ Works but expensive	✅ Ideal
User-uploaded media	⚠️ Works but not optimal	✅ Perfect
Application logs (active)	✅ Good	❌ Too slow
Log archives (>30 days old)	⚠️ Expensive	✅ Cost-effective
Static website assets	⚠️ Works	✅ Better (CDN)
Virtual machine disks	✅ Required	❌ Won’t work

Simple rule: If it needs a file system and low latency, use block storage. If it’s static content or archives, use object storage.

2. Plan Your Migration

• Backup first – Always create a dump before major changes
• Test in staging – If possible, practice on a non-production system
• Verify permissions – PostgreSQL is strict about ownership and permissions
• Monitor post-migration – Watch for at least a week before removing old data
• Document the process – Keep notes for future reference

3. Cost Comparison

For our 102GB PostgreSQL database:

Option	Setup Cost	Monthly Cost	Downtime	Risk	Performance
Expand root disk	$0	$40-80	15-30 min	Medium	Same
Object storage	N/A	N/A	N/A	Won’t work	N/A
Block storage	$0	$10-20	<5 min	Low	+15% better

Winner: Block storage provides the best combination of cost, performance, and risk.

4. Performance Considerations

Block storage on DigitalOcean Volumes offers:

• 3,000+ baseline IOPS – Suitable for most database workloads
• Sub-10ms latency – Excellent for transactional applications
• NVMe technology – Faster than traditional SSD
• Scalable to 100TB+ – Room for massive growth
• Snapshot capabilities – Backup without downtime

Perfect for PostgreSQL’s random I/O access patterns and B-tree index operations.

Conclusion

When our client faced a critical storage crisis with 102GB of data and a 98% full disk, the solution wasn’t to expand the server or attempt to use object storage—it was to leverage block storage.

Why block storage won:

1. Technical compatibility – PostgreSQL requires POSIX file system access
2. Performance requirements – Databases need <10ms latency, not 50-100ms
3. Cost-effectiveness – $10-20/month vs $40-80/month for server upgrade
4. Operational simplicity – Direct mount, no application changes needed
5. Future scalability – Easy to resize without downtime

Why object storage wasn’t suitable:

1. Not POSIX-compliant – Can’t be mounted as a file system
2. High latency – 50-100ms unsuitable for database operations
3. API overhead – HTTP requests for every operation create bottlenecks
4. No transactional guarantees – Eventual consistency incompatible with databases

By migrating PostgreSQL to dedicated block storage, we:

• Freed up critical root filesystem space (98% → 13%)
• Improved database performance by 15%
• Provided 105GB of room for future growth
• Saved $40-60/month compared to upgrading the server
• Completed migration with <5 minutes of downtime

The hybrid approach of using block storage for live databases and object storage for backups/static assets provides the best of both worlds—performance where you need it and cost-effectiveness where it matters.

Next Steps

If you’re facing similar storage challenges:

1. Assess your storage needs:

• Live databases → Block storage
• Backups and archives → Object storage
• Static content → Object storage with CDN

1. Plan your migration:

• Schedule maintenance window
• Create backups
• Test on staging if possible

1. Execute carefully:

• Follow the steps in this guide
• Verify permissions meticulously
• Test thoroughly before removing old data

1. Monitor and optimize:

• Watch performance metrics
• Set up automated backups to object storage
• Plan for future capacity needs

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Need Help with Your Database Migration?

If you’re facing storage challenges or need assistance migrating your databases to block storage, proper planning and execution can make the difference between a smooth migration and catastrophic data loss.

Understanding the difference between block storage and object storage—and choosing the right tool for each job—is fundamental to building scalable, performant, and cost-effective infrastructure.

Got questions about block vs object storage? Drop them in the comments below!