Annual A/B Test Storage vs Peak Retained Storage
Compare annual A/B testing data generation with peak retained capacity and see how retention and replication change storage estimates.
Annual generated storage measures the event volume produced over a year, while peak retained storage measures the data held at one time. Comparing both figures helps separate ingestion planning from active storage-capacity planning.
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About Annual A/B Test Storage vs Peak Retained Storage
Annual generated storage measures the event volume produced over a year, while peak retained storage measures the data held at one time. Comparing both figures helps separate ingestion planning from active storage-capacity planning.
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Key Factors
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365-day retention versus 90-day retention
The same experiment traffic and event payload are retained for different lengths of time.
| Factor | Option A: 365-Day Retention | Option B: 90-Day Retention | What It Means |
|---|---|---|---|
| Daily data ingestion | Unchanged | Unchanged | Retention does not change how much new event data is written each day. |
| Annual data generated | Same annual generation | Same annual generation | The experiment produces the same annual event payload at the same traffic and event rate. |
| Peak retained payload | About 365 days of data | About 90 days of data | A shorter active retention window holds fewer days of event records at one time. |
| Historical analysis window | Longer | Shorter | Longer retention leaves more historical event data available in the primary store. |
| Sensitivity to storage growth | Higher | Lower | More retained days cause the active data footprint to grow to a larger limit. |
Retention length does not alter daily ingestion or annual generation, but it directly determines the peak active event payload held in the primary store.
Replication factor 1 versus replication factor 3
The same event workload is stored with different numbers of copies.
| Factor | Option A: Replication Factor 1 | Option B: Replication Factor 3 | What It Means |
|---|---|---|---|
| Stored copies | One copy | Three copies | The appropriate number of copies depends on the storage architecture and resilience requirements. |
| Annual payload capacity | Base calculated volume | Three times base calculated volume | A lower replication factor consumes less raw payload capacity. |
| Peak retained payload | Base retention-window volume | Three times retention-window volume | Replication directly multiplies storage occupied by retained events. |
| Daily ingestion payload before copies | Same | Same | The calculator's daily data ingestion output is unreplicated, so it does not change with replication. |
| Copy redundancy | Lower | Higher | More stored copies provide more redundancy in the simplified model, though actual system behavior varies. |
Replication does not change the underlying event generation rate, but it multiplies both annual and peak retained payload storage.
Lean event tracking versus detailed event tracking
Two tracking designs have the same visitors but different event volume and average record size.
| Factor | Option A: Lean Tracking | Option B: Detailed Tracking | What It Means |
|---|---|---|---|
| Events per visitor | Fewer core events | More behavioral and diagnostic events | The appropriate event set depends on the analysis questions and instrumentation design. |
| Average record size | Usually smaller | May be larger | Fewer fields and smaller payloads generally reduce stored data size. |
| Daily storage ingestion | Lower | Higher | Daily payload rises with both event count and record size. |
| Analysis detail | More focused | Potentially broader | Detailed tracking can support additional analysis but may also capture unnecessary fields. |
| Storage estimate sensitivity | Lower sensitivity | Higher sensitivity | More events and larger records amplify the effect of traffic growth on storage. |
Event volume and record size are direct storage drivers, so tracking design can materially change both annual and peak capacity estimates.
Key Differences at a Glance
Annual storage represents data generated over 365 days, while peak retained storage represents data held at one point in time.
Retention changes peak retained capacity but does not change the daily event generation rate.
Replication multiplies annual and retained payload storage but does not change the calculator's unreplicated daily ingestion output.
Variant count affects the average traffic shown per variant, not total storage, when total visitors are split among variants.
Events per visitor and average event size directly scale every storage result.
How to Decide
Assumptions
- Comparisons hold daily visitor volume constant unless a row states otherwise.
- Event size is assumed to reflect the stored record after any applicable compression.
- Replication is modeled as a direct payload multiplier.
- The comparison does not model differences in storage-engine overhead or resilience behavior between platforms.
Related Comparisons
Frequently Asked Questions
Which result should be used for active storage capacity planning?
Peak retained storage is the closer payload estimate because it applies the selected retention window and replication factor.
Does reducing retention reduce annual data generation?
No. The same incoming event data may still be generated; shorter retention reduces how much remains in the active store at once.
Does a replication factor of 3 triple storage?
In this calculator's simplified model, yes. Annual and peak retained event payload are multiplied by three.
Is lower replication always better?
It uses less estimated payload capacity, but the suitable copy count depends on the storage system and operational requirements.
Should I choose lean or detailed event tracking based only on storage?
No. Storage is one trade-off. The required analysis, data quality, privacy practices, and system design also matter.
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