NoSQL Practice Exam

About NoSQL Exam

The Certificate in NoSQL exam evaluates candidates' proficiency in understanding, designing, and implementing NoSQL databases. This exam assesses participants' knowledge of various NoSQL database types, their use cases, data modeling techniques, query languages, and scalability considerations.

Skills Required

• Database Fundamentals: Understanding of database concepts, including data modeling, schema design, indexing, and querying.
• NoSQL Concepts: Proficiency in NoSQL database types, such as document-based, key-value, column-family, and graph databases.
• Data Modeling: Ability to design and implement NoSQL database schemas and data models for specific use cases.
• Querying and Indexing: Knowledge of querying techniques and indexing strategies in NoSQL databases to optimize performance.
• Scalability and Performance: Understanding of scalability considerations and strategies for distributed NoSQL databases.

Who should take the Exam?

The Certificate in NoSQL exam is suitable for database administrators, software engineers, data engineers, data architects, and anyone involved in designing, developing, or managing databases. This exam is ideal for individuals seeking to enhance their skills in NoSQL database technologies and applications.

Detailed Course Outline

The NoSQL Exam covers the following topics - 

Domain 1 - Introduction to NoSQL Databases

• Overview of NoSQL database types, characteristics, and use cases.
• Comparison of NoSQL databases with traditional relational databases.

Domain 2 - Document-based Databases

• Introduction to document-based NoSQL databases such as MongoDB, Couchbase, and CouchDB.
• Data modeling techniques for document-based databases, including schema design and document structures.

Domain 3 - Key-value Databases:

• Overview of key-value NoSQL databases such as Redis, Amazon DynamoDB, and Riak.
• Use cases and data modeling considerations for key-value databases.

Domain 4 - Column-family Databases:

• Introduction to column-family NoSQL databases such as Apache Cassandra, HBase, and ScyllaDB.
• Data modeling techniques for column-family databases, including wide-column design and partitioning strategies.

Domain 5 - Graph Databases:

Overview of graph NoSQL databases such as Neo4j, Amazon Neptune, and JanusGraph.

Graph data modeling techniques and query languages for analyzing interconnected data.

Domain 6 - Querying and Indexing in NoSQL Databases:

• Querying techniques and languages used in NoSQL databases, such as MongoDB Query Language (MQL) and Cassandra Query Language (CQL).
• Indexing strategies to optimize query performance in NoSQL databases.

Domain 7 - Scalability and Performance Considerations:

• Scalability considerations for distributed NoSQL databases, including sharding, replication, and consistency models.
• Performance tuning techniques for improving throughput and latency in NoSQL database deployments.