react-native-mmkv VS jina

react-native-mmkv is a wrapper around MMKV that allows you to easily implement secure storage in your app. It is arguably the fastest key-value storage for React Native apps

Why do you need to access the db from the file system? Can you just use something like https://github.com/mrousavy/react-native-mmkv ?

By using libraries like Reanimated, React Native MMKV, and React Native Skia, you leverage the native thread. However, I know there are developers building amazing things who think outside the box. I'm always thrilled when I read engineering blogs from companies like Netflix, Meta, and Shopify. They create solutions beyond the limits.

mmkv is not really designed to be used for “heavy” writes, or often changing values. But more as e.g. NSUserDefaults. The storage keeps growing over time which may cause memory issues if used wrongly. Here’s a related github issue: https://github.com/mrousavy/react-native-mmkv/issues/440

Persistence - React Native MMKV (supports encryption natively and easily integrates with TanStack Query via persistQueryClient)

if you need to store something small and simple use whatever. if is complex and speed is important use something performant. realmDB, https://github.com/mrousavy/react-native-mmkv and others are good fit for the job.

Screw you all, I'll use MMKV as my Local DB: please do not, as explained here.

Try react native mmkv https://github.com/mrousavy/react-native-mmkv

Jina mainly because of their use of neural networks and AI.

Jina - It’s an open-source project where you can build search engines. Well maybe not no code but it claims that you only need a few lines of code for creating projects. The project supports semantic, text, image, audio, and video search. What I’m also interested in is with their neural search and generative AI. I’m also interested in the amount of github repo that they have. I have this on my radar since this is also something I was interested in.

Do you guys have any ideas how we can match images on our database? We’re working on a project that about matching images on our database. We were trying to use SIFT and some other similar methods, but for some reason, nothing doesn’t seem to be working that well. Does anyone have any suggestions for the most effective way to do this? Maybe some open-source solutions like HuggingFace or Jina AI? We just want to make sure our image matching is correct and that part’s been a bit of a struggle on our part.

The tech lets you find 3D models without sifting through tons of text - An information retrieval framework does the heavy lifting and compares models to each other, no descriptions or keywords needed.

Jina AI -They offer a neural search solution that can help build smarter, more efficient search engines. They also have a list of cool github repos that you can check out. Similar to Vertex AI, they have image classification tools, NLPs, fine tuners etc.

Well, it's not exactly a new feature, but we've been working on early support for DocArray v2 in Jina.

Jina let’s you serve all of your models through the same Gateway while deploying them as individual microservices. You can also tie your models together in a pipeline if needed. Also some nice ML focussed features such as dynamic batching.