Database Size Estimator

About the Database Size Estimator

Estimating database size before deployment prevents the all-too-common scenario of running out of disk space in production. Database storage is more than just rows multiplied by row size—indexes, overhead structures, WAL/transaction logs, temporary space, and MVCC bloat all consume significant space. A database that looks like 10 GB of raw data can easily occupy 25–40 GB on disk.

This calculator models total database size by combining data volume (rows × row size), index overhead, page/block overhead, and a configurable general overhead factor. It also projects growth over time, giving you a multi-month capacity forecast. Use it for initial sizing, migration planning, or capacity reviews of existing databases.

When This Page Helps

Under-sizing database storage causes outages. Over-sizing wastes expensive SSD capacity. This calculator accounts for the overhead that raw data size alone misses, giving you an accurate estimate for procurement and capacity planning.

How to Use the Inputs

1. Enter the number of rows in your database.
2. Enter the average row size in bytes.
3. Enter the index overhead as a percentage of data size.
4. Enter the general overhead percentage (WAL, temp, MVCC).
5. Optionally enter monthly row growth for projection.
6. Review the estimated total database size.

Example Calculation

Tips & Best Practices

• PostgreSQL typically has 23 bytes of tuple header overhead per row; add this to your row size.
• B-tree indexes commonly add 30–60% overhead; multi-column and covering indexes add more.
• MVCC-based databases (PostgreSQL, Oracle) need extra space for dead tuples before VACUUM.
• WAL/transaction logs can consume 1–5 GB or more—provision this separately from data space.
• TOAST storage in PostgreSQL compresses and out-of-lines large columns, reducing effective row size.
• Run ANALYZE and check pg_total_relation_size() periodically to validate estimates against reality.

Sizing for Different Database Engines

PostgreSQL: Add 23 bytes per row for tuple header, plus 8 bytes page header per 8 KB page. MySQL InnoDB: Add 13–20 bytes per row for record header and row versioning. SQL Server: Add 7–14 bytes per row depending on nullable columns. Oracle: Add 3 bytes per row plus 24 bytes per block.

The 80% Rule

Never use more than 80% of available database storage. Above this threshold, auto-vacuum in PostgreSQL, index maintenance, and sort operations may fail due to insufficient temporary space. Plan your capacity alerts at 60%, 70%, and 80%.

Provisioning Cloud Database Storage

Cloud managed databases (RDS, Cloud SQL, Azure SQL) have maximum storage limits per instance type. Check that your projected growth stays within the instance's storage ceiling. Scaling storage is possible but may require downtime on some platforms.

Frequently Asked Questions

• What row size should I estimate?

  Sum the byte sizes of all columns: INT=4, BIGINT=8, VARCHAR(n)=average actual length +1–4 bytes overhead, TEXT=average length, TIMESTAMP=8, BOOLEAN=1, UUID=16. Add tuple header overhead (23 bytes for PostgreSQL, 8–16 bytes for MySQL).

• How much space do indexes use?

  A single B-tree index on an integer column uses about 30% of the table's size. A unique index is similar. Composite indexes and covering indexes use more. Total index overhead of 30–60% of data size is common for well-indexed OLTP tables.

• What should the overhead percentage include?

  General overhead covers WAL/redo logs (1–5 GB), temporary tablespace for sorts and joins, MVCC dead tuples (10–30% for PostgreSQL), page fill factor losses (typically 10–15%), and system catalogs. A 20–30% overhead factor is a good starting point.

• How does partitioning affect size?

  Table partitioning adds overhead for partition metadata and may reduce index efficiency slightly. However, it improves query performance on large tables and makes maintenance operations faster. The space overhead is typically under 1%.

• Should I size for peak or average usage?

  Size for peak. Databases need temporary space for sorts, hash joins, and maintenance operations. Provision at least 20% free space above your projected data size. Performance degrades significantly when disks approach 85–90% utilization.

• How do I estimate growth rate?

  Check your row insert rate (rows/day) and average row size. Multiply to get daily data growth. Factor in index growth proportionally. Track actual growth monthly and adjust projections. Most databases grow faster than initially estimated.