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NoSQL Deep Dive

Data SystemsNoSQL Databases🟒 Free Lesson

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Data Systems

NoSQL Deep Dive

NoSQL databases trade ACID guarantees for horizontal scalability and flexible data models. Master the four categories of NoSQL databases and their optimal use cases.

  • Scalability β€” Horizontal scaling across commodity servers
  • Flexibility β€” Schema-less or schema-on-read data models
  • Performance β€” Optimized for specific access patterns

NoSQL is not "No SQL"β€”it's "Not Only SQL." Choose the right tool for the job.

The Four Categories of NoSQL

DocumentMongoDB, CouchDBJSON/BSON documentsFlexible schemaNested dataKey-ValueRedis, DynamoDBO(1) lookupsHigh throughputSimple operationsColumn-FamilyCassandra, HBaseWide columnsWrite-optimizedTime-series dataGraphNeo4j, NeptuneNodes + edgesRelationship queriesTraversalsCommon NoSQL CharacteristicsHorizontal scalingEventual consistencyDenormalized dataSchema-on-readBASE propertiesTunable consistency

Document Databases (MongoDB)

MongoDB Internals

ComponentPurpose
WiredTigerStorage engine with document-level locking
B-tree indexesPrimary index structure
Replica SetPrimary-secondary replication for HA
ShardingHorizontal scaling across clusters
Aggregation PipelineServer-side data processing

Data Modeling Patterns

Key-Value Databases (Redis, DynamoDB)

Redis Data Structures

StructureUse CaseExample
StringCache, countersSET user:123 "Alice"
HashObject storageHSET user:123 name "Alice" age 30
ListMessage queuesLPUSH queue "msg1" "msg2"
SetTags, unique itemsSADD tags "python" "system-design"
Sorted SetLeaderboardsZADD leaderboard 100 "player1"
StreamEvent sourcingXADD events * type "click" page "/home"

DynamoDB Partitioning

Column-Family Databases (Cassandra)

Cassandra Data Model

Column Family: user_eventsuser_id (PK)timestampevent_typepropertiesuser_abcuser_abcuser_xyz

Cassandra Query Patterns

PatternDescriptionExample
Partition lookupGet all data for a partition keyWHERE user_id = 'abc'
Range within partitionQuery by clustering keyWHERE user_id = 'abc' AND timestamp > '2024-01-01'
Time-seriesLatest events for a userORDER BY timestamp DESC LIMIT 10

Graph Databases (Neo4j)

Graph Query Patterns

Query TypeDescriptionExample
Path findingShortest path between nodesFind 3-degree connections
Pattern matchingFind specific subgraphsUsers who bought X and Y
CentralityMost connected nodesInfluencer detection
Community detectionCluster related nodesSocial group identification

NoSQL Comparison Matrix

CriteriaDocumentKey-ValueColumn-FamilyGraph
Data modelJSON docsKey→ValueWide columnsNodes + edges
Query flexibilityHighLow (key only)ModerateHigh (traversals)
Write throughputGoodExcellentExcellentModerate
Read throughputGoodExcellentGoodDepends on query
Horizontal scalingGoodExcellentExcellentHard
ConsistencyConfigurableConfigurableTunableStrong
Best use caseContent managementCaching, sessionsTime-series, IoTSocial networks

Practice Exercises

  1. Data Modeling: Design the MongoDB schema for a blogging platform with users, posts, comments, and tags. Decide which fields to embed vs reference. Justify your choices.

  2. Key-Value Design: Using Redis, design a rate limiter that allows 100 requests per minute per user. What data structures would you use? How do you handle expiration?

  3. Column-Family Design: Design the Cassandra table schema for a time-series IoT sensor data system. What is the partition key? What is the clustering key?

  4. Graph Query: Given a social network graph, write the Cypher query to find "friends of friends who live in the same city and share at least 3 interests."


What to Learn Next

-> SQL Deep Dive PostgreSQL, MySQL, indexing strategies, and query optimization.

-> MongoDB Deep Dive Advanced MongoDB features, aggregation pipeline, and sharding.

-> Redis Deep Dive Redis data structures, persistence, clustering, and use cases.

-> Cassandra Deep Dive Cassandra architecture, data modeling, and operational patterns.

-> Choosing the Right Database Systematic framework for database selection.

-> DynamoDB Deep Dive DynamoDB internals, partitioning, and global tables.

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