Explore the structure, use cases, and benefits of document-oriented databases like MongoDB, focusing on flexible schemas and data storage as documents.
Explore the simplicity and high performance of key-value databases like Redis, understand data storage and retrieval using unique keys, and identify effective scenarios for key-value stores such as caching and real-time analytics.
Explore the power of graph databases like Neo4j in Clojure applications, focusing on nodes, relationships, and properties. Learn about use cases such as social networks, recommendation engines, and fraud detection.
Explore the benefits of using Datomic, including scalability, rich querying with Datalog, and data integrity through ACID transactions and schema enforcement.
Learn how to set up Datomic for scalable data solutions using Clojure, including installation, storage backend selection, and transactor configuration.
Explore the intricacies of defining schemas in Clojure using Datomic, focusing on attributes, entity types, and referential integrity for scalable NoSQL solutions.
Explore the power of time travel queries in Datomic using As-Of Queries and the History API to analyze data as it was at any point in time. Learn how to implement these features in Clojure for scalable data solutions.
Explore the fundamentals of Neo4j and graph theory, and discover how graph databases can revolutionize data storage and retrieval for complex, interconnected datasets.
Explore transaction support in NoSQL databases, focusing on MongoDB, Cassandra, and DynamoDB, with practical Clojure code examples and performance considerations.
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