Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache and message broker. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes with radius queries and streams. Redis has built-in replication, Lua scripting, LRU eviction, transactions and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster.
Based on our record, Redis should be more popular than Materialize. It has been mentiond 216 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Of course, these examples are just toys. A more proper use for asynchronous generators is handling things like reading files, accessing network services, and calling slow running things like AI models. So, I'm going to use an asynchronous generator to access a networked service. That service is Redis and we'll be using Node Redis and Redis Query Engine to find Bigfoot. - Source: dev.to / 13 days ago
Slap on some Redis, sprinkle in a few set() calls, and boom—10x faster responses. - Source: dev.to / 13 days ago
Real-time serving: Many push processed data into low-latency serving layers like Redis to power applications needing instant responses (think fraud detection, live recommendations, financial dashboards). - Source: dev.to / 26 days ago
Redis® Cluster is a fully distributed implementation with automated sharding capabilities (horizontal scaling capabilities), designed for high performance and linear scaling up to 1000 nodes. . - Source: dev.to / about 2 months ago
Instead of spinning up Redis, use an unlogged table in PostgreSQL for fast, ephemeral storage. - Source: dev.to / 2 months ago
It's hard to write something that is both accessible and well-motivated. The best uses of category theory is when the morphisms are far more exotic than "regular functions". E.g. It would be nice to describe a circuit of live queries (like https://materialize.com/ stuff) with proper caching, joins, etc. Figuring this out is a bit of an open problem. Haskell's standard library's Monad and stuff are watered down to... - Source: Hacker News / 5 months ago
> [...] `https://materialize.com/` to solve their memory issues [...] Disclaimer: I work at Materialize Recently there have been major improvements in Materialize's memory usage as well as using disk to swap out some data. I find it pretty easy to hook up to Postgres/MySQL/Kafka instances: https://materialize.com/blog/materialize-emulator/. - Source: Hacker News / 6 months ago
I agree. So many disparate solutions. The streaming sql primitives are by themselves good enough (e.g. `tumble`, `hop` or `session` windows), but the infrastructural components are always rough in real life use cases. Crossing fingers for solutions like `https://github.com/feldera/feldera` to solve their memory issues, or `https://clickhouse.com/docs/en/materialized-view` to solve reliable streaming consumption.... - Source: Hacker News / 6 months ago
Or the related Materialize stuff https://materialize.com/. - Source: Hacker News / 7 months ago
The original post makes so much more sense in this context! One of the "holy grails" in my mind is making CQRS and dataflow programming as easy to learn and maintain as existing imperative programming languages - and easy to weave into real-time UX. There are so many backend endpoints in the wild that do a bunch of things in a loop, many of which will require I/O or calls to slow external endpoints, transform the... - Source: Hacker News / 7 months ago
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
RisingWave - RisingWave is a stream processing platform that utilizes SQL to enhance data analysis, offering improved insights on real-time data.
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.
Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.