Anomaly detection is the process of identifying data points, entities or events that fall outside the normal range. An anomaly is anything that deviates from what is standard or expected. Humans and animals do this habitually when they spot a ripe fruit in a tree or a rustle in the grass ...
In a vector database, the vectors are typically stored along with their associated metadata, such as labels, identifiers, or any other relevant information. The database is optimized for efficient storage, retrieval, and querying of vectors based on their similarity or distance to other vectors. ...
Multi-model databasesare an emerging trend in both the NoSQL and RDBMS markets. They are designed to support multiple data models against a single, integrated backend. Most database management systems are organized around a single data model that determines how data can be organized, stored, and...
RDBMS stands for Relational Database Management System which stores data into tables, which consist of rows and columns. Learn What is RDBMS.
Vector Index vs. Vector Database Vector indexes and vector databases are both designed to efficiently store and retrievevectors, that is, sets of numbers that represent the features of an object, like a document, image, or video or audio file. However, they have different characteristics and us...
A Vector database is an innovative solution that has emerged to address the challenges posed by data representations in higher dimensions. In this blog, we’ll explore the concept, applications, benefits, and potential future of vector databases. Below are the following topics we are going to ...
In an MDB, sales could be viewed in the dimensions of the product model, geography, time or some additional dimension. In this case, sales is known as themeasure attributeof the data cube and the other dimensions are seen asfeature attributes. A database creator can definehierarchiesand level...
A vector database is an organized collection of vector embeddings that can be created, read, updated, and deleted at any point in time. Vector embeddings represent chunks of data, such as text or images, as numerical values. What is an Embedding Model?
The algorithms are then gathered in a pipeline to quickly and accurately retrieve and deliver data neighboring the vector that is queried. For example, an ANN search could look for products that are visually similar in an e-commerce catalog. Additional uses include anomaly detection, classification...
Common threats to data integrity Organizations face an increasingly complex landscape of threats to data integrity, ranging from unintentional human errors to sophisticatedcyber attacks. Understanding these threats is crucial for developing effective protection strategies and maintaining the trustworthiness of yo...