azure nosql
2 db cosmos db
Couchbase Features and Hybrid Architecture Use Cases
| Use Case | Handled by Couchbase Alone | Requires Hybrid Architecture with GPU |
|---|---|---|
| Image Storage and Retrieval | – Store images as binary data (e.g., base64-encoded) in Couchbase. <br>- Efficient querying and indexing using N1QL and Full-Text Search (FTS). <br>- Simple retrieval for display purposes. | – Not needed. |
| Metadata Management | – Store and retrieve image metadata (e.g., tags, descriptions) using JSON documents. <br>- Perform complex queries on metadata. | – Not needed. |
| Basic Image Processing | – Storing pre-processed images. | – Real-time image processing tasks like resizing, cropping, and filtering can benefit from GPU acceleration. |
| Image Classification | – Store pre-classified images and their labels. | – Training and running deep learning models for image classification require GPU acceleration for faster performance. |
| Object Detection | – Store detected objects’ metadata along with the images. | – Training and real-time inference for object detection models require GPUs for efficient processing. |
| Image Similarity Search | – Store feature vectors for images and use Full-Text Search for basic similarity search. <br>- Advanced similarity search can be enabled with vector storage and retrieval. | – Advanced similarity search using deep learning models to extract features and compare them requires GPUs. |
| Image Generation and Enhancement | – Store generated or enhanced images. | – Generative models (e.g., GANs) for image creation and enhancement need GPU acceleration for training and real-time processing. |
| Augmented Reality (AR) Applications | – Store AR-related data and metadata. | – Real-time image processing and overlay rendering for AR applications require GPU capabilities. |
| Video Frame Extraction | – Store individual frames extracted from videos as images. | – Real-time video frame extraction and processing require GPUs for efficient performance. |
| Face Recognition | – Store face embeddings and metadata. | – Training and real-time inference of face recognition models require GPU acceleration. |
| Image Compression and Decompression | – Store compressed images and metadata about compression. | – Real-time compression and decompression tasks benefit from GPU acceleration to handle large volumes of data quickly. |
| Image Annotation and Labeling | – Store annotated images and their labels in JSON documents. | – Automated or semi-automated image annotation using deep learning models can benefit from GPU acceleration for efficiency. |
| Medical Imaging Analysis | – Store medical images and related metadata. | – Advanced analysis of medical images (e.g., MRI, CT scans) using deep learning models requires GPUs for high performance and accuracy. |
| Geospatial Image Analysis | – Store geospatial images (e.g., satellite images) and metadata. | – Processing and analyzing geospatial data using machine learning models for tasks like land cover classification or change detection require GPU acceleration. |
| Storing Images as Vectors | – Store feature vectors of images for AI-driven tasks such as similarity search and classification. | – Extracting vectors from images using deep learning models and storing them for further AI applications require GPU acceleration for training and inference tasks. |
Summary
- Binary Storage: Directly stores image data for simple retrieval and display purposes. Ideal for straightforward storage and retrieval tasks.
- Vector Storage: Stores processed image data as vectors for advanced analysis and AI-driven applications. Requires preprocessing with machine learning models to convert images into feature vectors.
Key Points
- Binary Data: Suitable for applications where images need to be stored and retrieved without additional processing.
- Vector Data: Suitable for applications that require image analysis, similarity search, and machine learning functionalities.
https://chatgpt.com/share/8528e14f-4c63-4cf4-92f3-679ee0fb84dd
https://chatgpt.com/share/b02fc5ac-88af-441d-8527-5898bef47052
