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‎content/embeds/rdi-when-to-use.md‎

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## When to use RDI
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You should use RDI when:
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- You must use a slow database as the system of record for the app.
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- The app must always *write* its data to the slow database.
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- You already intend to use Redis for the app cache.
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- The data changes frequently in small increments.
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- Your app can tolerate *eventual* consistency of data in the Redis cache.
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- RDI throughput during
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[full sync]({{< relref "/integrate/redis-data-integration/data-pipelines#pipeline-lifecycle" >}}) would not exceed 30K records per second and during
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[CDC]({{< relref "/integrate/redis-data-integration/data-pipelines#pipeline-lifecycle" >}})
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would not exceed 10K records per second.
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## When not to use RDI
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You should *not* use RDI when:
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- You are migrating an existing data set into Redis only once.
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- Your app needs *immediate* cache consistency rather than *eventual* consistency.
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- The data is ingested from two replicas of Active-Active at the same time.
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- The app must *write* data to the Redis cache, which then updates the source database.
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- Your data set will only ever be small.
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- Your data is updated by some batch or ETL process with long and large transactions - RDI will fail
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processing these changes.
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## Decision tree for using RDI
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Use the decision tree below to determine whether RDI is a good fit for your architecture:
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```decision-tree {id="when-to-use-rdi"}
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id: when-to-use-rdi
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scope: rdi
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rootQuestion: systemOfRecord
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questions:
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systemOfRecord:
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text: |
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Does your app require a disk-based database as the system of record?
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whyAsk: |
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RDI is designed to keep Redis in sync with a primary database. If you don't need a primary database, RDI is not necessary.
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answers:
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yes:
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value: "Yes"
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nextQuestion: writeLocation
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no:
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value: "No"
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outcome:
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label: "RDI is not necessary for your use case"
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id: notNecessary
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sentiment: "negative"
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writeLocation:
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text: |
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Does your app write data directly to the disk-based database?
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whyAsk: |
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RDI requires the primary database to be the system of record. If your app writes to Redis first, RDI won't work.
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answers:
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yes:
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value: "Yes"
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nextQuestion: consistency
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no:
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value: "No"
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outcome:
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label: "RDI won't work - your app must write to the primary database"
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id: wrongWritePattern
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sentiment: "negative"
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consistency:
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text: |
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Can your app tolerate eventual consistency in the Redis cache?
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whyAsk: |
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RDI provides eventual consistency, not immediate consistency. If your app needs real-time cache consistency, RDI is not suitable.
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answers:
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yes:
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value: "Yes"
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nextQuestion: throughput
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no:
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value: "No"
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outcome:
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label: "RDI is not suitable - you need immediate cache consistency"
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id: needsImmediate
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sentiment: "negative"
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throughput:
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text: |
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Will your throughput stay within RDI limits (≤30K records/sec during full sync, ≤10K records/sec during CDC)?
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whyAsk: |
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RDI has throughput limits. Exceeding these limits will cause processing failures and data loss.
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answers:
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yes:
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value: "Yes"
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nextQuestion: dataPattern
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no:
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value: "No"
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outcome:
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label: "RDI throughput limits will be exceeded"
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id: exceedsLimits
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sentiment: "negative"
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dataPattern:
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text: |
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Is your data updated frequently in small increments (not by batch/ETL with large transactions)?
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whyAsk: |
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RDI captures changes from the database transaction log. Large batch transactions or ETL processes can cause RDI to fail.
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answers:
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yes:
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value: "Yes"
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nextQuestion: dataSize
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no:
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value: "No"
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outcome:
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label: "RDI will fail with batch/ETL processes and large transactions"
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id: batchProcessing
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sentiment: "negative"
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dataSize:
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text: |
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Is your data set large enough to benefit from caching?
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whyAsk: |
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RDI adds operational complexity. If your data set is small, you may not need caching at all.
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answers:
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yes:
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value: "Yes"
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nextQuestion: dataSource
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no:
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value: "No"
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outcome:
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label: "RDI is not necessary - your data set is too small"
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id: tooSmall
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sentiment: "negative"
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dataSource:
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text: |
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Is your data ingested from a single source (not from two Active-Active replicas simultaneously)?
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whyAsk: |
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RDI cannot handle data ingested from two Active-Active replicas at the same time, as this creates conflicting change events.
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answers:
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yes:
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value: "Yes"
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outcome:
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label: "✅ RDI is a good fit for your use case"
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id: goodFit
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sentiment: "positive"
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no:
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value: "No"
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outcome:
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label: "RDI won't work with Active-Active replicas"
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id: activeActive
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sentiment: "negative"
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```

‎content/integrate/redis-data-integration/when-to-use.md‎

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type: integration
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weight: 5
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---
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```decision-tree
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```
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RDI is designed to support apps that must use a disk based database as the system of record
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but must also be fast and scalable. This is a common requirement for mobile and web
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apps with a rapidly-growing number of users; the performance of the main database is fine at first
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but it will soon struggle to handle the increasing demand without a cache.
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## When to use RDI
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You should use RDI when:
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- You must use a slow database as the system of record for the app.
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- The app must always *write* its data to the slow database.
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- You already intend to use Redis for the app cache.
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- The data changes frequently in small increments.
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- Your app can tolerate *eventual* consistency of data in the Redis cache.
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- RDI throughput during
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[full sync]({{< relref "/integrate/redis-data-integration/data-pipelines#pipeline-lifecycle" >}}) would not exceed 30K records per second and during
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[CDC]({{< relref "/integrate/redis-data-integration/data-pipelines#pipeline-lifecycle" >}})
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would not exceed 10K records per second.
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## When not to use RDI
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You should *not* use RDI when:
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- You are migrating an existing data set into Redis only once.
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- Your app needs *immediate* cache consistency rather than *eventual* consistency.
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- The data is ingested from two replicas of Active-Active at the same time.
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- The app must *write* data to the Redis cache, which then updates the source database.
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- Your data set will only ever be small.
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- Your data is updated by some batch or ETL process with long and large transactions - RDI will fail
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processing these changes.
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## Decision tree for using RDI
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Use the decision tree below to determine whether RDI is a good fit for your architecture:
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```decision-tree {id="when-to-use-rdi"}
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id: when-to-use-rdi
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scope: rdi
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rootQuestion: systemOfRecord
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questions:
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systemOfRecord:
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text: |
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Does your app require a disk-based database as the system of record?
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whyAsk: |
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RDI is designed to keep Redis in sync with a primary database. If you don't need a primary database, RDI is not necessary.
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answers:
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yes:
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value: "Yes"
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nextQuestion: writeLocation
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no:
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value: "No"
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outcome:
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label: "RDI is not necessary for your use case"
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id: notNecessary
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sentiment: "negative"
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writeLocation:
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text: |
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Does your app write data directly to the disk-based database?
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whyAsk: |
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RDI requires the primary database to be the system of record. If your app writes to Redis first, RDI won't work.
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answers:
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yes:
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value: "Yes"
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nextQuestion: consistency
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no:
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value: "No"
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outcome:
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label: "RDI won't work - your app must write to the primary database"
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id: wrongWritePattern
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sentiment: "negative"
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consistency:
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text: |
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Can your app tolerate eventual consistency in the Redis cache?
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whyAsk: |
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RDI provides eventual consistency, not immediate consistency. If your app needs real-time cache consistency, RDI is not suitable.
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answers:
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yes:
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value: "Yes"
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nextQuestion: throughput
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no:
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value: "No"
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outcome:
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label: "RDI is not suitable - you need immediate cache consistency"
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id: needsImmediate
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sentiment: "negative"
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throughput:
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text: |
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Will your throughput stay within RDI limits (≤30K records/sec during full sync, ≤10K records/sec during CDC)?
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whyAsk: |
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RDI has throughput limits. Exceeding these limits will cause processing failures and data loss.
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answers:
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yes:
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value: "Yes"
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nextQuestion: dataPattern
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no:
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value: "No"
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outcome:
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label: "RDI throughput limits will be exceeded"
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id: exceedsLimits
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sentiment: "negative"
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dataPattern:
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text: |
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Is your data updated frequently in small increments (not by batch/ETL with large transactions)?
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whyAsk: |
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RDI captures changes from the database transaction log. Large batch transactions or ETL processes can cause RDI to fail.
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answers:
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yes:
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value: "Yes"
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nextQuestion: dataSize
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no:
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value: "No"
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outcome:
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label: "RDI will fail with batch/ETL processes and large transactions"
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id: batchProcessing
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sentiment: "negative"
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dataSize:
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text: |
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Is your data set large enough to benefit from caching?
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whyAsk: |
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RDI adds operational complexity. If your data set is small, you may not need caching at all.
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answers:
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yes:
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value: "Yes"
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nextQuestion: dataSource
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no:
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value: "No"
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outcome:
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label: "RDI is not necessary - your data set is too small"
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id: tooSmall
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sentiment: "negative"
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dataSource:
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text: |
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Is your data ingested from a single source (not from two Active-Active replicas simultaneously)?
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whyAsk: |
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RDI cannot handle data ingested from two Active-Active replicas at the same time, as this creates conflicting change events.
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answers:
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yes:
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value: "Yes"
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outcome:
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label: "✅ RDI is a good fit for your use case"
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id: goodFit
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sentiment: "positive"
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no:
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value: "No"
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outcome:
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label: "RDI won't work with Active-Active replicas"
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id: activeActive
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sentiment: "negative"
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```
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{{< embed-md "rdi-when-to-use.md" >}}

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