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Back in the day, when relational databases were choking on their own complexity and caching felt like an afterthought, along came Redis. It promised to be more than just a cache – a blazing-fast data structure server capable of handling anything from session management to pub/sub messaging. Quite clever, really, though one does wonder if the initial hype overstated its ability to replace everything.
In practice, Redis is fantastic at what it’s designed for: incredibly speedy access to key-value data. But scale it improperly, and you’ll quickly discover the limitations of an in-memory database. Memcached offers similar caching prowess, but Redis boasts richer data types and persistence options. Today, it’s a staple in modern stacks, powering everything from Netflix recommendations to real-time analytics—a testament to its speed, if not necessarily its all-conquering potential.
Used together with Redis
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Jobs in using Redis for but please no
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data scientist
AI / ML Platform Engineer @ whatnot-inc
US | 2025-12-28
| USD
225000 - 320000
/ year
Whatnot’s AI/ML Platform Engineer role promises building the infra that powers live-shopping AI—from low-latency large-model serving to distributed training on GPUs—while cohabiting with ML...
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AI/ML, LLM, Computer Science, Python, PostgreSQL, DynamoDB, ELK, Redis, Datadog, Grafana, Cloud Computing, AWS, Amazon SageMaker, AWS Lambda, Kinesis, S3, Amazon EC2, Kafka, Flink | ||
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| Marketing, Cloud Computing, CI/CD, Agile/Scrum, MongoDB, Redis, Datadog, Kubernetes, React |