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MongoDB C100DBA exam is a rigorous test that requires significant preparation. Candidates are expected to have a deep understanding of database administration concepts and be able to apply them to real-world scenarios. C100DBA Exam consists of multiple-choice questions and is timed, with a time limit of 90 minutes. Candidates must score at least 65% to pass the exam.
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Preparing for the MongoDB C100DBA exam requires a solid understanding of MongoDB architecture and administration. Candidates can prepare for the exam by taking MongoDB's official training courses, reading the MongoDB documentation, and practicing their skills on real-world MongoDB deployments. Passing the MongoDB C100DBA Exam is a valuable achievement for any database administrator who works with MongoDB and can open up new career opportunities.
NEW QUESTION # 20
What is the maximum size of Index Key Limit and Number of Indexes per collection?
Answer: D
NEW QUESTION # 21
In order to ensure that you can maintain high availability in the face of server failure, you should implement which of the following?
Answer: C
NEW QUESTION # 22
What command returns all documents in an orders collection where quantity is less than or equal to 1000 and salesRep is not equal to " Anne " ?
Answer: B
Explanation:
The quantity condition is "less than or equal to 1000," which maps to MongoDB ' s $lte comparison operator.
The sales representative condition is "not equal to Anne," which maps to $ne. When predicates on two different fields appear in the same query document, MongoDB applies an implicit logical AND, so both conditions must be true for a document to match. Option C therefore expresses exactly the requested filter: { quantity: { $lte: 1000 }, salesRep: { $ne: " Anne " } }. Options A and D use $neq, which is not MongoDB ' s inequality operator. Options B and D use $lt, which excludes documents whose quantity is exactly 1000 and therefore fails the "less than or equal" requirement. One nuance of $ne is that it can also match documents where the field is missing, because a missing field is not equal to the specified value. If the application requires salesRep to exist as well, an explicit existence predicate may be appropriate. For the wording shown, however, option C is the correct command.
Study Guide reference/topic:MongoDB Architecture and Core Operations - comparison predicates, $lte, $ne, and implicit AND semantics.
NEW QUESTION # 23
Consider a contacts collection that contains these documents:
{ " _id " : 1, " name " : " Poppy " , " birthday " : " 03-09-1984 " }
{ " _id " : 2, " name " : " Ashley " , " birthday " : " 08-12-1990 " }
{ " _id " : 3, " name " : " Cleo " , " birthday " : " 11-02-1976 " }
What query returns the document where the field name is " Poppy " ?
Answer: B
Explanation:
MongoDB equality filters use the form { field: value }. To return the document whose name field contains the exact string " Poppy " , the query therefore uses { name: " Poppy " }, as shown in option D. This shorthand equality syntax is equivalent to explicitly using $eq. Option B uses the correct field but the value is lowercase
" poppy " . Normal MongoDB string equality is case-sensitive unless a suitable collation or another case- insensitive technique is deliberately configured, so it does not match the displayed " Poppy " value. Option A uses name.Poppy as a dot-notation path. Dot notation is for accessing a nested field inside an embedded document, but here name stores a scalar string and has no nested Poppy field. Option C searches for a field literally named Poppy, which the sample documents do not contain. This question tests the basic field/value predicate syntax used by find(). The correct command is db.contacts.find({ " name " : " Poppy " }), making option D correct.
Study Guide reference/topic:MongoDB Architecture and Core Operations - find(), equality predicates, string matching, and dot notation.
NEW QUESTION # 24
What is the purpose of enabling TLS?
Answer: C
Explanation:
Transport Layer Security protects MongoDB network communications while data travels between clients and servers and, when configured, between MongoDB deployment members. Its core purpose is therefore encryption of data in transit. TLS helps prevent passive interception and tampering and also supports certificate-based identity validation. It is separate from encryption at rest, which protects files on storage media, and separate from Queryable Encryption or client-side field encryption, which protects selected application data before it reaches the server. Option A is unrelated: backup and restore operations use snapshot, managed backup, or database-tool mechanisms. Option B describes the objective of replication, elections, and redundant deployment architecture, not TLS. Option C is also incorrect; TLS is a security control, not a query-optimization mechanism, and cryptographic processing can add some overhead rather than improving query execution. A secure MongoDB deployment normally combines TLS with strong authentication, least-privilege authorization, appropriate network exposure controls, auditing, and storage or field-level encryption as required. For the specific question, enabling TLS provides encryption for data moving across the network, making option D correct.
Study Guide reference/topic:Security, Networking, and Encryption - TLS/SSL, transport encryption, certificates, and network security.
NEW QUESTION # 25
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