Vector Databases: Weaviate
Weaviate is an open-source search engine powered by machine learning. It specializes in vector search and storage.
Key features of Weaviate can be enumerated as follows:
1. Contextual Search Capabilities:
A must for any vector DB, Weaviate employs machine learning models (variant of transformer architecture) to understand the context of the data through a combination of semantic and
2. Automatic Vectorization:
Weaviate automatically converts data into vectors. In other words, we do not need to manually convert our data into vectors. It helps in handling large volumes of data, and enables more efficient and scalable data processing and analysis.
3. Scalability:
Weaviate is designed to scale horizontally. It handles increasing amount of data by adding more machines to the network. Scalability is essential for applications that generate large volumes of data. Weaviate’s architecture ensures that performance does not degrade as the dataset grows.
4. Real-time Indexing:
Weaviate indexes data in real-time — a vital feature for applications that require up-to-date…
