5 great ways to reimagine your data layer
summary
Redis Enterprise replaces a cobbled AWS stack (Kinesis, DynamoDB, ElastiCache, Timestream, OpenSearch plus Lambdas) with a single multi‑model platform using streams, JSON, RediSearch, time series, graph and Bloom filters to collect, index, queue and analyze data. It claims sub-millisecond reads and writes, Active‑Active geo distribution for global deployments, 99.999% uptime, Redis on Flash to cut infra costs up to ~80%, and unified multi‑cloud/hybrid deployment so performance, scale and cost tradeoffs are reduced.
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chapters (10)
- 0:00Intro
- 0:45What is Redis?
- 1:31What is the data layer?
- 2:38Who is responsible for the data layer?
- 6:07Complexity
- 7:58Pioneering a full real-time data platform
- 9:202. Unifying the cache and primary database
- 10:15Providing flexibility to deploy anywhere
- 11:19Delivering enterprise-grade performance
- 12:35Eliminating performance/cost tradeoffs
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