Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Turnkey Multi-Region, Active-Active Session Stores with Steeltoe, Redis Enterprise, and PAS

77 views

Published on

SpringOne Platform 2019
Session Title: Turnkey Multi-Region, Active-Active Session Stores with Steeltoe, Redis Enterprise, and PAS
Speaker: Adi Foulger, Principal Solution Architect, Redis Labs
Youtube: https://youtu.be/8IkZRzyRc1c

Published in: Technology
  • Be the first to comment

  • Be the first to like this

Turnkey Multi-Region, Active-Active Session Stores with Steeltoe, Redis Enterprise, and PAS

  1. 1. Global Multi-Model Databases with Steeltoe and PCF ADI FOULGER | October 2019
  2. 2. $ whoami E-mail: adi.foulger@redislabs.com LinkedIn: whois.redis.ninja
  3. 3. An In-memory open source database, supporting a variety high performance operational, analytics or hybrid use case Our Roots Are in Open Source
  4. 4. Redis Enterprise An in-memory multi-model database built on top of open source Redis
  5. 5. Real Time Analytics User Session Store Real Time Data Ingest High Speed Transactions Job & Queue Management Time Series Data Complex Statistical Analysis Notifications Distributed Lock Content Caching Geospatial Data Streaming Data Machine Learning Search Uniquely Suited to Modern Use Cases A full range of capabilities that simplify and accelerate next generation applications
  6. 6. Data Structures - Redis’ Building Blocks 6 Lists [ A → B → C → D → E ] Hashes { A: “foo”, B: “bar”, C: “baz” } Bitmaps 0011010101100111001010 Strings "I'm a Plain Text String!” Bit field {23334}{112345569}{766538} Key ”Retrieve the e-mail address of the user with the highest bid in an auction that started on July 24th at 11:00pm PST” ZREVRANGE 07242015_2300 0 0= Streams 🡪{id1=time1.seq1(A:“xyz”, B:“cdf”), d2=time2.seq2(D:“abc”, )}🡪 Hyperloglog 00110101 11001110 Sorted Sets { A: 0.1, B: 0.3, C: 100 } Sets { A , B , C , D , E } Geospatial Indexes { A: (51.5, 0.12), B: (32.1, 34.7) }
  7. 7. Multi-Model Functionality at Any Scale • Dedicated engine for each data model (vs. API only) • Models engines can be selectively loaded, according to use case • All model engines access the same data, eliminating the need for transferring data between them
  8. 8. Redis Enterprise Technology 8 Redis Enterprise Node Redis Enterprise Cluster • Shared nothing cluster architecture • Fully compatible with open source commands & data structures
  9. 9. High Performance Read and write with low local sub-millisecond latency Guaranteed data consistency CRDT based: The datatypes are conflict-free by design. All databases eventually converge automatically to the same state with strong eventual consistency Supports causal consistency executing read and write operations in an order that reflects causality Simplifies the app design Develop as if it’s a single app in a single geo, we take care of all the rest Redis Enterprise Delivers Strong Eventual Consistency and Causal Consistency 9
  10. 10. Multi-Cloud and Hybrid Cloud-OnPrem Support App App App App Active-Active or Active-Passive
  11. 11. Multi-Cloud and Hybrid Cloud-OnPrem Support Causal Consistency
  12. 12. CRDT Example: Counter 12 Applies Commutative and Associative Properties K = 30 + 40 + 50 = 120 K = 40 + 30 + 50 = 120 K = 50 + 30 + 40 = 120 INCR K 50 INCR K 30INCR K 40 A B C Time: t1
  13. 13. CRDT Example: Set 13 Applies idempotence Star Wars Coco Wonder Women Star Wars A B C Time: t1
  14. 14. Causal Consistency 14 Based on a Directed Acyclic Graph model. DAGs can only be traversed in one direction, no matter their shape.
  15. 15. Redis CRDTs : Per Key Causal Consistency Hot Replica A Apple Replica B Replica C Apple Apple Pie Hot Pie Peach? Source FIFO 15 Replica A Apple Replica B Replica C TastyHot Apple Pie Hot Pie Causal consistency Apple
  16. 16. Reference Architecture
  17. 17. Thank you!

×