Big Data & Tools with NoSQL
  • Big Data & Tools
  • ReadMe
  • Big Data Overview
    • Overview
    • Job Opportunities
    • What is Data?
    • How does it help?
    • Types of Data
    • The Big 4 V's
      • Variety
      • Volume
      • Velocity
      • Veracity
      • Other V's
    • Trending Technologies
    • Big Data Concerns
    • Big Data Challenges
    • Data Integration
    • Scaling
      • CAP Theorem
      • Optimistic concurrency
      • Eventual consistency
      • Concurrent vs. Parallel Programming
    • Big Data Tools
    • No SQL Databases
    • What does Big Data learning means?
  • Linux & Tools
    • Overview
    • Linux Commands - 01
    • Linux Commands - 02
    • AWK
    • CSVKIT
    • CSVSQL
    • CSVGREP
  • Data Format
    • Storage Formats
    • CSV/TSV/Parquet
    • Parquet Example
    • JSON
    • HTTP & REST API
      • Terms to Know
        • Statefulness
        • Statelessness
        • Monolithic Architecture
        • Microservices
        • Idempotency
    • REST API
    • Python
      • Setup
      • Decorator
      • Unit Testing
      • Flask Demo
      • Flask Demo - 01
      • Flask Demo - 02
      • Flask Demo - 03
      • Flask Demo - 04
      • Flask Demo - 06
    • API Testing
    • Flask Demo Testing
    • API Performance
    • API in Big Data World
  • NoSQL
    • Types of NoSQL Databases
    • Redis
      • Overview
      • Terms to know
      • Redis - (RDBMS) MySql
      • Redis Cache Demo
      • Use Cases
      • Data Structures
        • Strings
        • List
        • Set
        • Hash
        • Geospatial Index
        • Pub/Sub
        • Redis - Python
      • Redis JSON
      • Redis Search
      • Persistence
      • Databases
      • Timeseries
    • Neo4J
      • Introduction
      • Neo4J Terms
      • Software
      • Neo4J Components
      • Hello World
      • Examples
        • MySQL: Neo4J
        • Sample Transactions
        • Sample
        • Create Nodes
        • Update Nodes
        • Relation
        • Putting it all together
        • Commonly used Functions
        • Data Profiling
        • Queries
        • Python Scripts
      • More reading
    • MongoDB
      • Sample JSON
      • Introduction
      • Software
      • MongoDB Best Practices
      • MongoDB Commands
      • Insert Document
      • Querying MongoDB
      • Update & Remove
      • Import
      • Logical Operators
      • Data Types
      • Operators
      • Aggregation Pipeline
      • Further Reading
      • Fun Task
        • Sample
    • InfluxDB
      • Data Format
      • Scripts
  • Python
    • Python Classes
    • Serialization-Deserialization
  • Tools
    • JQ
    • DUCK DB
    • CICD Intro
    • CICD Tools
      • CI YAML
      • CD Yaml
    • Containers
      • VMs or Containers
      • What container does
      • Podman
      • Podman Examples
  • Cloud Everywhere
    • Overview
    • Types of Cloud Services
    • Challenges of Cloud Computing
    • High Availability
    • Azure Cloud
      • Services
      • Storages
      • Demo
    • Terraform
  • Data Engineering
    • Batch vs Streaming
    • Kafka
      • Introduction
      • Kafka Use Cases
      • Kafka Software
      • Python Scripts
      • Different types of Streaming
    • Quality & Governance
    • Medallion Architecture
    • Data Engineering Model
    • Data Mesh
  • Industry Trends
    • Roadmap - Data Engineer
    • Good Reads
      • IP & SUBNET
Powered by GitBook
On this page
  1. NoSQL
  2. Redis

Terms to know

PreviousOverviewNextRedis - (RDBMS) MySql

Last updated 1 year ago

The Redis server is the heart of the Redis system, handling all data storage, processing, and management tasks.

  • A simple database, i.e., a single primary shard.

  • A highly available (HA) database, i.e., a pair of primary and replica shards.

  • A clustered database contains multiple primary shards, each managing a subset of the dataset.

  • An HA clustered database, i.e., multiple pairs of primary/replica shards.


Shard: Splitting data across multiple Redis instances to distribute load and data volume. It's like breaking a big dataset into smaller, manageable pieces.

Cluster: A group of Redis nodes that share data. Provides a way to run Redis where data is automatically sharded across nodes.

Replication is copying data from one Redis server to another for redundancy and scalability. The primary server's data is replicated to one or more secondary (replica) servers.

Multi-Model Database

Redis-Core - Key-Value Store Extend with Redis Modules Redis Search - Elastic Search RedisGraph - Graph Database RedisJSON - Document Database RedisTimeSeries - TimeSeries Database

Transactions: Grouping commands to be executed as a single isolated operation, ensuring atomicity.

Pipeline: Bundling multiple commands to reduce request/response latency. Commands are queued and executed at once.

Transactions: Grouping commands to be executed as a single isolated operation, ensuring atomicity.

Remember: [A]CID in MySQL? It's either all or nothing. For example, Transfer money from A to B.

Persistence: Saving data to disk for durability. Redis offers RDB (snapshotting) and AOF (logging every write operation).

RDB (Redis Database)

RDB periodically creates point-in-time snapshots of your dataset at specified intervals. It is generally faster for larger datasets because it doesn't write every disk change, reducing I/O overhead.

AOF (Append Only File)

Durability: Records every write operation received by the server. You can configure the fsync policy to balance between durability and performance.

Data Loss Risk: Less risk of data loss compared to RDB. It can be configured to append each operation to the AOF file as it happens or every second.

Recovery Speed: Slower restarts compared to RDB because Redis replays the entire AOF to rebuild the state.