Redis: a Multi-Model DB for IoT and Beyond...•Redis OSS with Streams + Modules-Time...

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Redis: a Multi-Model DB for IoT and Beyond Dr. Christoph Zimmermann November 2020

Transcript of Redis: a Multi-Model DB for IoT and Beyond...•Redis OSS with Streams + Modules-Time...

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Redis: a Multi-Model DB for IoT and Beyond

Dr. Chr i s toph Z immermann

November 2020

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1. Introduction

2. Multi-modal Redis

3. Use cases

4. Wrap-up / Q&A

Overview

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•PhD in reflective operating system architectures

•First crush on Linux: kernel 0.95

•Tech support + more @ FraLUG

•Arch package maintainer

•Hobbies include:

-Community liaison / solution architect @ Redis Labs-SDLC-IT security and other forms of black art

Dr. Christoph Zimmermann

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linuxinlaws.eu

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Our Roots Are in Open Source

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An In-memory open source database, supporting a variety high performance operational, analytics or hybrid use case

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The Redis Community

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172CLIENTS IN 53 LANGUAGES

100+HIGHER LEVEL LIBRARIES

AND TOOLS

9.8K+GITHUB COMMITS

500+CONTRIBUTORS

48.6K+STACK OVERFLOW

QUESTIONS

46K+REDIS GITHUB STARS

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Hashes

Bitmaps

Strings

Bit field

Streams

Hyperloglog

Sorted Sets

Sets

Geospatial

Search

Graph

TimeSeries

AI

JSON

Gears

Redis Modules

Linearly Scalable HA Geo-Distributed Durable ACID Tiered-Memory Secured

BloomFilter

Redis Enterprise

Redis and its ecosystem

Lists

Redis Native Data Structures

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• Redis OSS with Streams + Modules-Time Series-Graph-AI-Gears

• Small Footprint-<5 MB footprint-Multi-platform: ARM32, ARM64, x64

• High Performance for large and fast data at the edge-Real-time data ingress from sensor network-<1ms processing latency at the edge-Tunable data persistence-Multi-model for servicing multiple data models

RedisEdge for the IoT Edge

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+

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Hybrid Deployment

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Redis Data Structures

RedisTimeSeries

Redis Streams

Data Egress

RedisAIData Ingress

Data

Commands

Data

Commands

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Data Analytics

Event Detection

Message Passing

Asset Management

Cloud-agnostic deployment

RedisEdge

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•OpenCypher compatible Graph DB extension

•Efficient storage in sparse matrices

•Fast GraphBLAS-based implementation

•Performance gain: 10x – 50x compared to industry leader

•Clients available:

-Compiler-Based: Rust, Golang, Java-Other: Python, JavaScript, Ruby, PHP

Module Case Study: RedisGraph

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Demo time

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• Flexible multi-model in-memory DB• From Edge right to scalable cloud deployments•Edge, X-platform:-From embedded to pot. FPGAs•Comprehensive ecosystem:-Module SDK (any P/L supporting C bindings incl. Rust)-Rich client-side environment

Conclusion

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Questions & answers

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Thank You!

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Dr. Christoph Zimmermannchristoph at redislabs dot com