Large-document merging, simultaneous edits and background indexing. Time the job and identify CPU, storage or external-service waits before replacing hardware.
Imports, processing and simultaneous users.Requisitos de hardware de AFFiNE: RAM, CPU, almacenamiento y fusión de documentos y PostgreSQL
Planifica la RAM, la CPU, el almacenamiento persistente y las dependencias de servicio de AFFiNE, con dimensionamiento de ZimaOS según la carga de trabajo, copias de seguridad y opciones de hardware prácticas.
AFFiNE hardware requirements at a glance
AFFiNE server demand grows with document size, edit history, synchronization and uploaded blobs. Its published recommendations distinguish basic usage from larger documents.
- RAM
- 2 GB recommended for basic use; 4 GB for larger documents.
- CPU
- At least 4 cores recommended.
- Storage
- About 1.5 GB for installation alone; add database, blobs and backups.
- Required services
- PostgreSQL and Redis are required; optional monitoring and search add separate memory and disk demand.
- Main sizing variable
- Large-document merging, simultaneous edits and background indexing.
- Practical Zima starting point
- ZimaBoard 2 1664 with SSD-backed active state is an editorial starting point for modest use. Include the OS and all companion services; it is not a measured capacity guarantee.
From official requirements to the right setup
Plan the complete AFFiNE workload before selecting a server.
-
Official requirements
Choose the exact edition, stable release and supported container/runtime. PostgreSQL and Redis are required; optional monitoring and search add separate memory and disk demand.
-
Confirm your needs
Test a representative busy operation: Large-document merging, simultaneous edits and background indexing. Record peak resident memory, CPU, disk latency and completion time, including other containers.
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Leave room to grow
Place active state on reliable persistent storage. PostgreSQL, blob storage, configuration and generated keys, with consistent database/blob backups. Budget working space for an upgrade or import and test recovery before relying on the deployment.
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Run it on ZimaOS
On ZimaOS, use a compatible amd64 container through Custom Install and reproduce all required services, volume mappings and device access. Do not treat an external AI API or local inference engine as part of the basic collaboration-server footprint.
Check every playback client
- Exact edition and stable release
- Compatible amd64 image/runtime
- All required companion services
- Realistic peak activity
- Persistent data and file ownership
- Free host ports and reachable URLs
- Working space and backup retention
- Successful database/file restore
Official minimum requirements
Reviewed October 30, 2026 against the linked upstream deployment documentation. Numerical values retain their stated minimum, recommendation or example scope; select release-compatible instructions before installation.
Use the requirements and scope above as a starting point, then validate AFFiNE under its real workload. Application examples, build-time settings and per-container limits are not interchangeable with a whole-server minimum.
| Requirement | Official minimum | What this supports |
|---|---|---|
| RAM guidance | 2 GB recommended for basic use; 4 GB for larger documents. | Official guidance keeps its original test, recommendation or example scope. |
| CPU guidance | At least 4 cores recommended. | Core counts do not predict a fixed user, device or document capacity. |
| Storage planning | About 1.5 GB for installation alone; add database, blobs and backups. | Installation space is separate from retained content, working files and backups. |
| Service topology | PostgreSQL and Redis are required; optional monitoring and search add separate memory and disk demand. | Include every stateful companion service in the host budget. |
| Persistent state | PostgreSQL, blob storage, configuration and generated keys, with consistent database/blob backups. | An image rebuild or container replacement is not a backup. |
| Deployment boundary | Do not treat an external AI API or local inference engine as part of the basic collaboration-server footprint. | Check the linked project instructions for the selected edition and release. |
When to upgrade your hardware
Use observed AFFiNE workload pressure to decide when an upgrade is warranted.
Busy operations exceed the available window
The complete stack runs short of memory
Persistent data approaches available capacity
Inspect the application and each required service for OOM events, sustained swap or growing queues. Reduce unnecessary concurrency before adding capacity.
Shared hosts and background work.PostgreSQL, blob storage, configuration and generated keys, with consistent database/blob backups. Track primary state and backup retention separately.
Long-lived installations and growing collections.Plan hardware growth with confidence
Address storage, memory, compute and deployment limits separately.
Use suitable active storage
Put latency-sensitive application/database state on durable local SSD storage and keep recoverable copies.
SATA or PCIe SSD according to measured data growth.Add memory for the complete stack
Choose a higher-RAM host when peak application and companion-service usage leaves inadequate OS headroom.
ZimaBoard 2 1664 or ZimaCube 2 Pro according to the measured constraint.Separate capacity from compute
A multi-drive system helps when retained content and backup storage are the problem; it is not automatically a faster application.
ZimaCube 2 when a broader multi-drive workload justifies it.Fix the observed bottleneck
Do not treat an external AI API or local inference engine as part of the basic collaboration-server footprint.
Check service configuration, I/O and network behavior before selecting a stronger CPU.Can it run on ZimaOS?
A matching current entry was not found in the reviewed official ZimaOS store source. Treat this as a Custom Install candidate and verify the selected upstream image, required services and host access.
Custom install AFFiNE in ZimaOS
PostgreSQL and Redis are required; optional monitoring and search add separate memory and disk demand. Persist: PostgreSQL, blob storage, configuration and generated keys, with consistent database/blob backups.
Custom install AFFiNE in the ZimaOS app ↗Use the official AFFiNE deployment instructions
Keep the selected stable release, persistent paths and companion services aligned with upstream documentation.
Review AFFiNE official installation ↗Check workload-specific deployment details
Do not treat an external AI API or local inference engine as part of the basic collaboration-server footprint.
Review AFFiNE deployment details ↗Which Zima hardware fits AFFiNE?
Start with the lowest reasonable host for the actual workload. Product specifications were checked against the current product pages.
Which workload best matches your AFFiNE deployment?
Modest AFFiNE deployment
Start with durable active data and a measured whole-stack memory budget.
- Workload optionZimaBoard 2 1664
Heavier jobs or more companion applications
Choose added memory or compute only when observed peaks justify the change.
- Workload optionZimaCube 2 Pro
These are practical workload recommendations, not official app requirements, compatibility certification, measured capacity limits or performance guarantees. Include all co-hosted services and independent backups.
| Zima hardware | Best for | Example workload | Core configuration | Recommended boundary | Next step |
|---|---|---|---|---|---|
| ZimaBoard 2 1664 | Modest AFFiNE workload | Large-document merging, simultaneous edits and background indexing. |
|
This is an editorial host choice, not an official app minimum or a guaranteed user/device capacity. | Get Now |
| ZimaCube 2 Pro | More processing or shared-service headroom | PostgreSQL and Redis are required; optional monitoring and search add separate memory and disk demand. |
|
Size the combined stack and active working set; more RAM does not fix remote API limits or missing dependencies. | Get Now |
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Frequently asked questions
Answers to AFFiNE RAM, CPU, storage, Docker, database and ZimaOS sizing questions.
How much RAM should I plan for AFFiNE?
2 GB recommended for basic use; 4 GB for larger documents. Include ZimaOS, the application and its companion services rather than reserving the entire machine for one container.
What drives the CPU requirement?
At least 4 cores recommended. The workload to test is: Large-document merging, simultaneous edits and background indexing.
Which data must survive a container update?
PostgreSQL, blob storage, configuration and generated keys, with consistent database/blob backups. Preserve a consistent database/file set and verify that your recovery procedure restores a working application.
What other services belong in the budget?
PostgreSQL and Redis are required; optional monitoring and search add separate memory and disk demand.
Does this workload need a dedicated GPU?
A dedicated GPU is not assumed for the core workflow described here. Optional AI, acceleration or media-processing integrations must be evaluated separately against the selected backend.
Can I deploy it on ZimaOS?
Use an amd64 container and the current upstream service topology through Custom Install when a suitable maintained image is available. Container availability alone is not a compatibility certification.
What should I check before upgrading hardware?
Do not treat an external AI API or local inference engine as part of the basic collaboration-server footprint. Compare CPU saturation, memory pressure, disk latency and external-service waits during the same reproducible operation.
Which Zima device is a practical starting point?
ZimaBoard 2 1664 is the editorial starting point for this modest deployment. Choose ZimaCube 2 Pro for measured memory/processing pressure or broader shared services; retained data determines storage expansion.
What sources informed this AFFiNE hardware guide?
This guide was reviewed against the linked project deployment documentation on October 30, 2026. Zima device choices are editorial workload guidance, separate from upstream requirements and measured performance.
