node-redis
Milvus
node-redis | Milvus | |
---|---|---|
12 | 105 | |
16,688 | 26,979 | |
0.3% | 2.5% | |
7.9 | 10.0 | |
4 days ago | 3 days ago | |
TypeScript | Go | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
node-redis
- Vector database built for scalable similarity search
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JavaScript + Database ?
Probably redis.
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Superfast search with RediSearch
Did you have an overdose of theory? Let us now taste some code that can help us apply some concepts. This example focuses on the text search. Redis provides us with a straightforward command line interface, along with useful SDK modules in most common languages. Below is a JavaScript code that uses Node Redis module to communicate with the Redis Server. Along with the JavaScript code, we can see the corresponding CLI commands. We need a text-rich dataset to save in our database and demonstrate the search functionality. For this, we will use a dump of poems obtained from Kaggle. The JSON chunk can be found on this link.
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client is closed
You need to call and await the connect method on your clients before you can send commands. For an example, see the sample usage code in the project README.
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IP Visualizer, development process or from total jank to less jank ;)
First thing to deal with is getting the data (using the GeoLite2 free geolocation data from MaxMind) into Redis so can actually query it. This was easier said than done. I used the node-redis lib and well, all the geo stuff in this lib are broken af (mildly speaking).
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Using Redis Cloud in your NextJS application
30 maximum connections may not seem like an issue as long as you are not building an application that has specific requirements for concurrency. This statement could be true if we are establishing connections between a Node server and a Redis cache since it is recommended that only one or two Redis client would be instantiated then reused in the Node server. In this case, there is a limited number of connections (clients are connections in Redis) needed when the server is running and communicating with Redis.
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Show HN: Postgres.js – Fastest Full-Featured PostgreSQL Client for Node and Deno
> Sure, the c++ is going to require you to do some sanitizing as you force your data into v8
it's not just sanitizing, there's a lot more to the object creation inside v8 itself. but, even if it were just sanitizing, that mechanism has become a lot more complicated than it ever was in v8 3.1 (timeframe around node 0.4) or 3.6 (timeframe around node 0.6). when interacting with c++, v8 makes no assumptions, whereas when interacting with javascript, a large number of assumptions can be made (e.g. which context and isolate is it being executed in, etc).
> but as we noted that's inevitable no matter how you slice it.
yes, from c++ to javascript and back, but when you need to make that trip multiple times, instead of once, that interchange adds up to quite a bit of extra code executed, values transformed, values checked, etc. sure, banging your head against a wall might not hurt once, but do it 40 times in a row and you're bound to be bloodied.
> Now maybe in some cases the v8 internals offer some advantages the generic c++ api can't access
by a fairly large margin, as it turns out, especially as v8 has evolved from the early 3.1 days to the current 9.8: 11 years. there has been significant speedup to javascript dealing with javascript objects compared to c++ dealing with javascript objects. see below.
> My memories of the redis client is different than yours so I'd be quite interested to see those conversations / benchmarks.
super easy to find, all of that was done in public: https://github.com/redis/node-redis/pull/242 - there are multiple benchmarks done by multiple people, and the initial findings were 15-20% speedup, but were improved upon. the speedup was from the decoding of the binary packet, which was passed as a single buffer, as opposed to parsing it externally and passing in each object through the membrane.
> As a simple thought experiment, in the scenario you're describing we should see a javascript implementation of a JSON parser to beat the pants off the v8 engine implementation, but this doesn't seem to the case.
that's a bit of a straw man argument. especially given that JSON.parse() is a single call and does not require any additional tooling/isolates/contexts to execute, it's just straight c++ code with very fast access into the v8 core:
Local result = Local::New(isolate, JSON.Parse(jsonString));
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Release 0.4: Progressing
I actually found 2 resources which might be useful to help me in setting the ttl expire period for the key: Redis-doc and issue-100 and I wil be dig in to it in couple days to figure it out
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How to create LinkedIn-like reactions with Serverless Redis
The easiest way to connect Redis with Upstash is to use the redis-client as described here.
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Host and Use Redis for Free
After filling out the project details, cd into your project and install redis, a Node.js client for Redis, and dotenv, an environment variable loader.
Milvus
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Computer Vision Meetup: Develop a Legal Search Application from Scratch using Milvus and DSPy!
Legal practitioners often need to find specific cases and clauses across thousands of dense documents. While traditional keyword-based search techniques are useful, they fail to fully capture semantic content of queries and case files. Vector search engines and large language models provide an intriguing alternative. In this talk, I will show you how to build a legal search application using the DSPy framework and the Milvus vector search engine.
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Ask HN: Who is hiring? (April 2024)
Zilliz (zilliz.com) | Hybrid/ONSITE (SF, NYC) | Full-time
I am part of the hiring team for DevRel
NYC - https://boards.greenhouse.io/zilliz/jobs/4307910005
SF - https://boards.greenhouse.io/zilliz/jobs/4317590005
Zilliz is the company behind Milvus (https://github.com/milvus-io/milvus), the most starred vector database on GitHub. Milvus is a distributed vector database that shines in 1B+ vector use cases. Examples include autonomous driving, e-commerce, and drug discovery. (and, of course, RAG)
We are also hiring for other roles that I am not personally involved in the hiring process for such as product managers, software engineers, and recruiters.
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Unlock Advanced Search Capabilities with Milvus and Read about RAG
Get started with Milvus on GitHub.
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Milvus VS pgvecto.rs - a user suggested alternative
2 projects | 13 Mar 2024
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How to choose the right type of database
Milvus: An open-source vector database designed for AI and ML applications. It excels in handling large-scale vector similarity searches, making it suitable for recommendation systems, image and video retrieval, and natural language processing tasks.
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Simplifying the Milvus Selection Process
Selecting the right version of open-source Milvus is important to the success of any project leveraging vector search technology. With Milvus offering different versions of its vector database tailored to varying requirements, understanding the significance of selecting the correct version is key for achieving desired outcomes.
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7 Vector Databases Every Developer Should Know!
Milvus is an open-source vector database designed to handle large-scale similarity search and vector indexing. It supports multiple index types and offers highly efficient search capabilities, making it suitable for a wide range of AI and ML applications, including image and video recognition, natural language processing, and recommendation systems.
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Ask HN: Who is hiring? (February 2024)
Zilliz is hiring! We're looking for REMOTE and/or HYBRID roles in SF
Zilliz is the company behind Milvus (https://github.com/milvus-io/milvus), the most widely adopted vector database. Vector databases are a crucial piece of any technology stack looking to take advantage of unstructured data. Most recently and notably, Retrieval Augmented Generation (RAG). For RAG, vector databases like Milvus are used as the tool to inject customized data. In other words, vector databases make things like customized chat bots, personalized product recommendations, and more possible.
We are hiring for Developer Advocates, Senior+ Level Engineers and Product people, and Talent Acquisition. Check out all the roles here: https://zilliz.com/careers
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Qdrant, the Vector Search Database, raised $28M in a Series A round
Good on them, I know the crustaceans are out here happy about this raise for a Rust based Vector DB!
(now I'm gonna plug what I work on)
If you're interested in a more scalable vector database written in Go, check out Milvus (https://github.com/milvus-io/milvus)
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Open Source Advent Fun Wraps Up!
But before we do, I do want to say that 🤩 all these lovely Open-Source projects would love a little 🎉💕 love by getting a GitHub star ⭐ for their efforts. Including Open Source Milvus 🥰
What are some alternatives?
redis-modules-sdk-ts - A Software development kit for easier connection and execution of Redis Modules commands.
pgvector - Open-source vector similarity search for Postgres
dotenv - Loads environment variables from .env for nodejs projects.
faiss - A library for efficient similarity search and clustering of dense vectors.
RedisInsight - Redis GUI by Redis
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
upstash-redis - HTTP based Redis Client for Serverless and Edge Functions
Weaviate - Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
bull-board - 🎯 Queue background jobs inspector
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
Face Recognition - The world's simplest facial recognition api for Python and the command line