C100DEV Drivers, Tools, Transactions, and Search Practice Question
A developer is configuring an Atlas Search index on a collection of product documents. The index definition uses a dynamic mapping. Which two statements accurately describe the behavior or configuration of Atlas Search indexes in this scenario? (Choose two.)
⚠ Common exam trap
The trap here is assuming dynamic mapping indexes every field including _id and requires explicit analyzers, when it actually skips certain fields and applies defaults automatically.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Atlas Search indexes are stored in a separate search process and are updated asynchronously from the primary replica set.
Dynamic mapping in Atlas Search automatically indexes supported field types without per-field declarations, and the search index itself is maintained by a separate process that receives changes asynchronously from the replica set. The other statements misstate requirements or availability: analyzers are not mandatory for every string under dynamic mapping, Atlas Search is unavailable outside Atlas, and underscore-prefixed fields like _id are not dynamically indexed.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Dynamic mappings index fields whose names begin with an underscore, such as _id, by default.
Why it's wrong here
Atlas Search dynamic mappings do not index the _id field by default, nor do they generally index fields starting with an underscore. The _id field is excluded from dynamic indexing to avoid unnecessary index bloat and because it is not typically a search target. If a developer needs to search on such a field, an explicit field mapping is required, which contradicts the assumption that dynamic mapping covers it automatically.
- ✓
Atlas Search indexes are stored in a separate search process and are updated asynchronously from the primary replica set.
Why this is correct
Atlas Search uses a dedicated search process that maintains its own index separate from the MongoDB data files. Changes from the replica set are replicated to the search process and applied asynchronously, so there can be a brief delay between a write and its visibility in $search results. This architecture keeps search workloads isolated from the primary's storage engine while still reflecting changes through the oplog.
- ✗
Atlas Search indexes can be created on any MongoDB deployment, including self-managed community servers.
Why it's wrong here
Atlas Search is a feature of MongoDB Atlas and is not available on self-managed community servers or on-premises deployments. Attempting to create a search index outside Atlas is not supported by the tooling. The developer must be working within an Atlas cluster, and in some cases a dedicated search node tier, for Atlas Search indexes to be created and queried.
- ✓
A dynamic mapping automatically indexes all dynamically indexable field types in each document, including strings, numbers, and dates.
Why this is correct
Dynamic mapping in Atlas Search inspects each document and indexes fields whose types are supported for dynamic indexing, such as strings, numbers, booleans, and dates. This removes the need to enumerate every field in the index definition. It is the default behavior when no explicit field mappings are provided, and it is why a newly created dynamic index can immediately support $search queries across many fields without further configuration.
- ✗
Setting dynamic to true requires also specifying analyzers for every string field in the collection.
Why it's wrong here
Dynamic mapping does not require per-field analyzer declarations. When dynamic is true, Atlas Search applies default analyzers to string fields unless an explicit mapping overrides them. Requiring analyzers for every string field would defeat the purpose of dynamic mapping, which is to index fields automatically. The developer can still add custom analyzers, but they are optional, not mandatory, under a dynamic configuration.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official MongoDB exam blueprint
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