Data Deduplication Savings Calculator
Estimate the storage space and cost savings you can achieve with data deduplication technology.
Calculation Results
'; outputHTML += 'Required Storage Space: ' + requiredStorage.toFixed(2) + ' ' + dataUnit + ''; outputHTML += 'Total Space Saved: ' + spaceSaved.toFixed(2) + ' ' + dataUnit + ''; outputHTML += 'Storage Savings Percentage: ' + savingsPercentage.toFixed(1) + '%'; resultDiv.innerHTML = outputHTML; resultDiv.style.display = 'block'; }What is Data Deduplication?
Data deduplication is a specialized data compression technique for eliminating duplicate copies of repeating data in storage systems. The goal is to improve storage utilization, which can lead to significant cost savings. Instead of storing multiple identical blocks of data, a deduplication system stores only one unique instance and replaces all other instances with a pointer to that single copy.
How to Use the Deduplication Calculator
Our calculator helps you quantify the potential benefits of implementing a deduplication solution. Here's how to use it:
- Total Data Size: Enter the total amount of data you need to store before any deduplication is applied. This could be the size of your full backups, your virtual machine farm, or your file shares.
- Data Unit: Select the appropriate unit for your data size: Gigabytes (GB), Terabytes (TB), or Petabytes (PB).
- Expected Deduplication Ratio: This is the most critical factor. It represents how much data reduction you expect. A ratio of 10:1 means that for every 10 units of original data, only 1 unit of storage space will be consumed. This ratio varies widely based on the type of data.
Understanding Deduplication Ratios
The effectiveness of deduplication is measured by its ratio. A higher ratio means greater savings. Here are some typical, real-world examples of deduplication ratios:
- Virtual Machine (VDI) Images: Often see very high ratios, from 10:1 to 50:1 or more, because many VMs are created from the same base operating system image.
- Full Backups: Subsequent full backups of the same systems can achieve high ratios (e.g., 20:1) because most of the data remains unchanged between backups.
- General File Servers: Ratios are typically lower, perhaps in the 3:1 to 8:1 range, as user files tend to be more unique.
- Encrypted or Pre-compressed Data: This data yields very poor ratios, often close to 1:1, because the data is already randomized and unique.
Practical Example
Let's say a company needs to store backups for a file server with 50 TB of data. They perform a full backup every week. Because much of the data is redundant from week to week, they estimate a conservative deduplication ratio of 8:1.
- Original Data Size: 50 TB
- Deduplication Ratio: 8:1
Using the calculator, we find:
- Required Storage: 50 TB / 8 = 6.25 TB
- Space Saved: 50 TB – 6.25 TB = 43.75 TB
- Savings Percentage: 87.5%
By implementing deduplication, the company reduces its storage requirement from 50 TB to just 6.25 TB, freeing up a massive amount of capacity and significantly lowering the cost of its backup storage infrastructure.
Types of Deduplication
Deduplication can be implemented in different ways, each with its own trade-offs:
- Inline vs. Post-Process: Inline deduplication analyzes and removes redundant data before it is written to disk. Post-process deduplication writes the data first and then analyzes it for duplicates later. Inline saves more space immediately, while post-process requires a larger initial landing zone but can be less performance-intensive during data ingestion.
- Source vs. Target: Source deduplication happens on the client or server creating the data (e.g., a backup agent) before it's sent over the network. This saves network bandwidth. Target deduplication happens on the storage device itself after receiving the data.