MongoDB Atlas Online Archive
Parent: MongoDB Atlas · Published reference · snapshot 2026-09-08 · skill mongodb-atlas-expert/references/mongodb-atlas-online-archive.md
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Online Archive automatically moves documents matching an archival rule out of the live Atlas cluster into Atlas-managed object storage, while keeping those documents queryable through the cluster's FD
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Overview
- Online Archive automatically moves documents matching an archival rule out of the live Atlas cluster into Atlas-managed object storage, while keeping those documents queryable through the cluster's FDI endpoint (transparent to the application). [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#overview]
Requirements
- Dedicated cluster M10+ (not available on M0/Flex/Serverless) [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#requirements]
- MongoDB 5.0+ on the source cluster [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#requirements]
DATE (most common)
- dateFormat options: "ISODATE" (default ISODate), "EPOCH_MILLISECONDS", "EPOCH_SECONDS" [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#date-most-common]
Partition Fields Strategy
- Partition fields organize archived data into S3 prefix paths for efficient filtering. Critical for query performance. Choose fields commonly used in query filters: [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#partition-fields-strategy]
- Maximum 2 partition fields per archive rule [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#partition-fields-strategy]
- First field MUST match the dateField (for DATE criteria) or be the most selective filter field (for CUSTOM criteria) [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#partition-fields-strategy]
- Order matters: highest-selectivity filter field should be first [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#partition-fields-strategy]
- Supported partition pruning operators: $eq, $gt, $lt, $gte, $lte, $ne, $in [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#partition-fields-strategy]
- Fields NOT in partitionFields trigger full archive scan when queried [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#partition-fields-strategy]
Archive Job Timing & Processing
- Runs every 5 minutes [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#archive-job-timing-processing]
- Max throughput: 2 GB per 5-minute interval [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#archive-job-timing-processing]
- Max file size: 100 MB per archive file [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#archive-job-timing-processing]
- Documents deleted from live cluster AFTER successful write to object storage [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#archive-job-timing-processing]
- Schedule window: Archive jobs can be limited to off-hours to reduce production impact [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#archive-job-timing-processing]
Query Routing
- When querying via the cluster's FDI endpoint: [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#query-routing]
- Recent data → live cluster (fast, indexed) [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#query-routing]
- Archived data → Online Archive object storage (slower, partition-based) [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#query-routing]
- Combined queries → both, results merged transparently [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#query-routing]
- Applications do not need to change query patterns after data is archived - same connection string, same MQL. [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#query-routing]
Cost Model
- $5/TB cost applies when QUERYING archived data. Storage itself is much cheaper than cluster storage (NVMe/GP3). [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#cost-model]
- Minimum: 10 MB per archive query (no benefit from very small queries). [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#cost-model]
Restore / Rehydration
- Archive data is immutable (append-only). To restore to the live cluster: [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#restore-rehydration]
Limitations
- No updates/deletes on archived data: Archive is immutable object storage; updateMany or deleteMany against archived documents will not affect them [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#limitations]
- No Atlas Search on archived data: Full-text $search doesn't work on archived data [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#limitations]
- No indexes on archived data: All archived queries use partition pruning only [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#limitations]
- $sample not random: Returns first N documents, not a statistical random sample [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#limitations]
- No transactions crossing live+archive: Cannot span a transaction across live and archived documents [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#limitations]
- Maximum query timeout: 6 hours (inherits from Data Federation limit) [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#limitations]
Archive Not Moving Data
- Check Atlas → Online Archive → [collection] → Activity tab for job status and errors [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#archive-not-moving-data]
- Verify dateField name is exact (case-sensitive) and matches documents [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#archive-not-moving-data]
- Confirm correct dateFormat - ISODATE requires actual ISODate values, not Unix epoch integers [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#archive-not-moving-data]
- Confirm cluster tier is M10+ and MongoDB version 5.0+ [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#archive-not-moving-data]
Archive Backlog Growing
- Archive jobs process 2 GB per 5-minute window [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#archive-backlog-growing]
- If data accumulates faster than 2 GB/5 minutes, backlog will grow [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#archive-backlog-growing]
- Mitigation: narrow the archive rule to reduce concurrent archiving volume, or contact MongoDB for higher throughput [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#archive-backlog-growing]
Slow Archive Queries
- Partition fields not aligned with query filter → full archive scan [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#slow-archive-queries]
- Check partitionFields match the most common query filter fields [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#slow-archive-queries]
- Run explain() on the FDI endpoint to check nPartitionsScanned [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#slow-archive-queries]
MACC / Cost Tracking
- Archive storage costs appear on the Atlas invoice under Tools & Services → Online Archive. Query processing costs under Data Federation. Monitor in Atlas Billing → Current Invoice. [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#macc-cost-tracking]
Anti-Patterns
- Choosing partition fields that don't match query patterns: Full archive scan on every query → high $5/TB cost [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#anti-patterns]
- Using CUSTOM criteria without an index on the filter field: Archive job itself will do slow scans to find matching documents - add an index on filter fields [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#anti-patterns]
- Querying archived data without partition-aligned filters: Always include a partition field in $match when querying archive [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#anti-patterns]
- Expecting consistency between live and archive: Documents are copied to archive and then deleted from live - there is no transactional guarantee between the two [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#anti-patterns]
- Using Online Archive as a backup system: Archive only stores the final document state at archival time - not a substitute for backup snapshots with PITR [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#anti-patterns]
References
- Online Archive Documentation [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#references]
- Configure an Online Archive [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#references]
- Query Archived Data [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#references]
- Online Archive Billing [archived source: https://llms-explorer.com/sources/mdb-context-hub/mongodb-atlas-online-archive/#references]
Where this helps
- Reducing live-cluster storage cost for time-based data, such as event logs or historical orders, that's rarely queried after a certain age, without changing application query patterns. [source] — AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.
- Meeting a data-retention requirement where old data must remain queryable but doesn't need to sit on expensive cluster storage. [source] — AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.
- Designing partition fields so archived-data queries stay fast instead of triggering a full archive scan. [source] — AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.
- Deciding Online Archive is the wrong tool because the use case actually needs a real backup with PITR, not an archive. [source] — AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.
Project ideas
- Configure an Online Archive rule on a DATE field with well-chosen partition fields matching the most common query filter, then run explain() on the FDI endpoint to check nPartitionsScanned. [source] — AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.
- Build a query-routing test that confirms combined live+archive queries return merged results through the same connection string and MQL the application already uses. [source] — AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.
- Set up a CUSTOM-criteria archive rule with a supporting index on the filter field, and compare archive job throughput against a DATE-based rule. [source] — AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.
- Build a cost dashboard tracking the $5/TB archived-data query charge separately from Online Archive storage cost, using the Atlas Billing Dashboard. [source] — AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.
Common mistakes
- Choosing partition fields that don't match actual query filters, forcing a full archive scan, and the associated $5/TB cost, on every query. [source] — AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.
- Using CUSTOM archive criteria without an index on the filter field, which makes the archive job itself do slow scans to find matching documents. [source] — AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.
- Assuming transactional consistency between live and archived data — documents are copied to archive storage and then deleted from the live cluster, with no transactional guarantee linking the two. [source] — AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.
- Treating Online Archive as a backup — it only stores the final document state at archival time, so it's not a substitute for PITR-backed snapshots. [source] — AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.
Known issues
- Archived data is immutable — updateMany or deleteMany against archived documents has no effect, and there is no in-place update path. [source] — AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.
- There is no Atlas Search or index support on archived data; all archived queries rely purely on partition pruning. [source] — AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.
- $sample against archived data is not a true random sample — it returns the first N documents rather than a statistically random selection. [source] — AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.
- Archive job throughput is capped at 2 GB per 5-minute interval, so a source collection generating archival-eligible data faster than that will build a growing backlog. [source] — AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.
Children
- Archive Rules
- Partition Fields
- Federated Query on Archive (frontier)
- Archive Cost Model (frontier)
- Archive Restore (frontier)
- Archive Monitoring (frontier)
- Archive Anti-Patterns (frontier)
Frontier under this node: Archive Anti-Patterns, Archive Cost Model, Archive Monitoring, Archive Restore, Federated Query on Archive