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 seems to be a lot more popular than LangChain. While we know about 218 links to Redis, we've tracked only 4 mentions of LangChain. 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.
Picture this: you've just built a snappy web app, and you're feeling pretty good about it. You've added Redis to cache frequently accessed data, and your app is flying—pages load in milliseconds, users are happy, and you're a rockstar. But then, a user updates their profile, and… oops. The app still shows their old info. Or worse, a new blog post doesn't appear on the homepage. What's going on? Welcome to the... - Source: dev.to / about 7 hours ago
Valkey and Redis streams are data structures that act like append-only logs with some added features. Redisson PRO, the Valkey and Redis client for Java developers, improves on this concept with its Reliable Queue feature. - Source: dev.to / 6 days ago
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 / 20 days ago
Slap on some Redis, sprinkle in a few set() calls, and boom—10x faster responses. - Source: dev.to / 20 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 / about 1 month ago
Undoubtedly, LangChain is the most popular framework for AI application development at the moment. The advent of LangChain has greatly simplified the construction of AI applications based on Large Language Models (LLM). If we compare an AI application to a person, the LLM would be the "brain," while LangChain acts as the "limbs" by providing various tools and abstractions. Combined, they enable the creation of AI... - Source: dev.to / about 1 year ago
Developed using Langchain and Streamlit technologies for enhanced performance. - Source: dev.to / about 1 year ago
LangChain was first released in October 2022 as an open-source side project, a framework that makes developing AI applications more flexible. It got so popular that it was promptly turned into a startup. - Source: dev.to / about 1 year ago
Being able to plug third party frameworks (Langchain, LlamaIndex) so you can build complex projects. - Source: dev.to / over 1 year ago
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Haystack NLP Framework - Haystack is an open source NLP framework to build applications with Transformer models and LLMs.
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.
Dify.AI - Open-source platform for LLMOps,Define your AI-native Apps
Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.
Hugging Face - The AI community building the future. The platform where the machine learning community collaborates on models, datasets, and applications.