🗄️ NoSQL Databases for Data Engineers

    Explore NoSQL database types including document stores, key-value stores, column-family databases, and graph databases.

    Level:
    Intermediate
    Tools:
    MongoDB
    Redis
    Cassandra
    Neo4j
    DynamoDB

    Skills You'll Learn:

    Document stores
    Key-value stores
    Column-family stores
    Graph databases
    CAP theorem
    When to use NoSQL

    Step 1: NoSQL Fundamentals

    • 1Understand the motivation behind NoSQL databases and their history
    • 2Learn the four main categories of NoSQL databases: document, key-value, column-family, and graph
    • 3Compare NoSQL schema-on-read with relational schema-on-write approaches
    • 4Understand denormalization and why NoSQL databases embrace data duplication
    • 5Identify real-world use cases where NoSQL outperforms relational databases

    Step 2: Document Databases (MongoDB)

    • 1Install MongoDB and connect using the shell or MongoDB Compass
    • 2Create databases, collections, and insert documents with nested structures
    • 3Query documents using find, filters, projections, and the aggregation pipeline
    • 4Design document schemas for embedded vs referenced relationships
    • 5Use indexes to optimize read performance on common query patterns

    Step 3: Key-Value Stores (Redis)

    • 1Install Redis and connect using redis-cli
    • 2Work with core data types: strings, hashes, lists, sets, and sorted sets
    • 3Implement caching patterns using TTL (time-to-live) expiration
    • 4Use Redis pub/sub for simple real-time messaging between services
    • 5Understand Redis persistence options (RDB snapshots vs AOF) and their trade-offs

    Step 4: Column-Family Stores (Cassandra)

    • 1Understand Cassandra's distributed architecture and the concept of a ring topology
    • 2Define keyspaces and tables using CQL (Cassandra Query Language)
    • 3Design partition keys and clustering keys for efficient data distribution
    • 4Model data around query patterns instead of entity relationships
    • 5Understand replication strategies and tunable consistency levels

    Step 5: Graph Databases (Neo4j)

    • 1Understand the property graph model: nodes, relationships, and properties
    • 2Install Neo4j and explore the browser interface
    • 3Write Cypher queries to create, read, update, and delete graph data
    • 4Traverse relationships using variable-length path queries
    • 5Identify use cases where graph databases excel: recommendations, fraud detection, and social networks

    Step 6: CAP Theorem and Consistency Models

    • 1Understand the CAP theorem: Consistency, Availability, and Partition tolerance
    • 2Learn the difference between strong consistency, eventual consistency, and causal consistency
    • 3Map popular NoSQL databases to their CAP trade-offs (CP vs AP)
    • 4Understand quorum reads and writes and how they tune consistency

    Step 7: Choosing the Right Database

    • 1Evaluate access patterns: read-heavy, write-heavy, or mixed workloads
    • 2Consider data shape: nested documents, flat key-value, wide rows, or connected graphs
    • 3Assess scalability requirements: vertical vs horizontal scaling
    • 4Compare managed cloud offerings: DynamoDB, Cosmos DB, Cloud Bigtable, and Amazon Neptune
    • 5Practice choosing the right database for three different real-world scenarios

    Recommended Resources

    MongoDB University

    course
    Visit →

    Redis Documentation

    documentation
    Visit →

    Apache Cassandra Documentation

    documentation
    Visit →

    Ready to Apply Your Knowledge?

    Put these fundamental concepts into practice with our hands-on projects and structured roadmaps.