nosql

## What I do - Choose appropriate NoSQL databases for use cases - Design distributed data models - Optimize for specific access patterns - Handle eventual consistency - Design for horizontal scalability ## When to use me When selecting NoSQL databases, designing distributed systems, or working with non-relational data models. ## Key Concepts ### NoSQL Categories - **Document**: MongoDB, CouchDB, Cosmos DB - **Key-Value**: Redis, DynamoDB, etcd - **Wide-Column**: Cassandra, HBase, Bigtable - **Graph**: Neo4j, Amazon Neptune, ArangoDB ### Data Modeling Patterns - Denormalization - Embedding vs referencing - Composite keys - Time-series modeling - Event sourcing patterns ### Consistency Models - Eventual consistency - Strong consistency - Tunable consistency - Read your writes consistency - Causality and vector clocks ### Scalability - Horizontal partitioning (sharding) - Consistent hashing - Data balancing - Replication topologies - Multi-region deployments ### Query Patterns - Primary key access patterns - Secondary indexes - Full-text search - Aggregation pipelines - Graph traversal ### Trade-offs - ACID vs BASE - CAP theorem implications - Query flexibility vs performance - Schema flexibility vs validation ## When to Use Each Type - **Document**: Flexible schemas, catalogs, content management - **Key-Value**: Caching, session store, high-speed access - **Wide-Column**: Time-series, IoT, high write throughput - **Graph**: Social networks, recommendations, fraud detection