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Mr. Kishor B. Parkhe
M. Tech. (Mathematics)
Feature Of Redis
 Read – fast
 Write – faster
 Number Of Set operation – 100000 per seconds
 Bulk Insertion

 Use REST API
 Atomicity
 Transaction like Rollback

 Able to process 32k-40k requests per second
Data Structure
 Hash – different than MongoDB, CouchBase
 List – Queues, Stack
 Set – All set Operation
 Blocking Queues

 Expiry Mechanism for Cache
Redis Cluster Managements
 Simple to Configured
 Durability
 Snapshots
 Priority to store

 Master Slave Relation
Redis Cache Service
Master
Request

Response
Application
Server 1

Slave 1

Application
Server 3

Application
Server 2

Application
Server 4

Slave 2

Redis Distributed Cluster

Cache Service Users
Weakness of Redis
 Loss of data
 Redis does not Support larger datasets than RAM
Conclusion
 Suitable for cache if RAM is not issue.
 Distributed and Centralizes as service.
 Better than Mem-cache.
 Infrastructure will not commodity hardware.

 Near Real Time Cache.
Stats
 Number inquiry in Minute= 900
 Recall size= 4000 per inquiry (worse case)
 Inquiries per second= 15
 Number of request for Redis= 15 * 4000 (worse case)

 Number of request for Redis= 60k
 Time Ratio= 3:2
Thanks

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Redis

  • 1. Mr. Kishor B. Parkhe M. Tech. (Mathematics)
  • 2. Feature Of Redis  Read – fast  Write – faster  Number Of Set operation – 100000 per seconds  Bulk Insertion  Use REST API  Atomicity  Transaction like Rollback  Able to process 32k-40k requests per second
  • 3. Data Structure  Hash – different than MongoDB, CouchBase  List – Queues, Stack  Set – All set Operation  Blocking Queues  Expiry Mechanism for Cache
  • 4. Redis Cluster Managements  Simple to Configured  Durability  Snapshots  Priority to store  Master Slave Relation
  • 5. Redis Cache Service Master Request Response Application Server 1 Slave 1 Application Server 3 Application Server 2 Application Server 4 Slave 2 Redis Distributed Cluster Cache Service Users
  • 6. Weakness of Redis  Loss of data  Redis does not Support larger datasets than RAM
  • 7. Conclusion  Suitable for cache if RAM is not issue.  Distributed and Centralizes as service.  Better than Mem-cache.  Infrastructure will not commodity hardware.  Near Real Time Cache.
  • 8. Stats  Number inquiry in Minute= 900  Recall size= 4000 per inquiry (worse case)  Inquiries per second= 15  Number of request for Redis= 15 * 4000 (worse case)  Number of request for Redis= 60k  Time Ratio= 3:2

Notas del editor

  1. Remote Dictionary Service
  2. All Stats are theoretically.