This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
In the illustration below, we are showing how different types of applications can access a database using REST API. Layered System: REST API should be designed in a layered systemarchitecture, where each layer has a specific role and responsibility. Code on Demand : REST API supports the execution of code on demand.
Store these chunks in a vector database, indexed by their embedding vectors. The various flavors of RAG borrow from recommender systems practices, such as the use of vector databases and embeddings. Here’s a simple rough sketch of RAG: Start with a collection of documents about a domain. Split each document into chunks.
We often see how inattention to the law can twist systemarchitectures. If an architecture is designed at odds with the development organization's structure, then tensions appear in the software structure. 1: The source for Conway's law is an article written by Melvin Conway in 1968.
In this article, well explore the essential skills and knowledge you need to become a successful blockchain developer. By spreading out data storage, blockchain reduces the vulnerability associated with centralized points of failure typical in traditional databases. The robustness of blockchain lies in its permanence.
It gives instant access to insights on over 10,000 companies from hundreds of thousands of proprietary intel articles, helping financial institutions make informed credit decisions while effectively managing risk. This integrated workflow provides efficient query processing while maintaining response quality and system reliability.
IBM Power Virtual Servers ( PowerVS) are a cutting-edge Infrastructure-as-a-Service (IaaS) offering designed specifically for businesses looking to harness the power of IBM Power Systemsarchitecture. Performance and reliability: PowerVS leverages IBM Power Systemsarchitecture, known for its outstanding performance and reliability.
Summary: Oracle’s Exalytics, Exalogic, and Exadata transform enterprise IT with optimised analytics, middleware, and databasesystems. Introduction This article explores Oracles engineered systemsExalytics, Exalogic, and Exadatahighlighting their transformative role in modern IT infrastructure.
Tools range from data platforms to vector databases, embedding providers, fine-tuning platforms, prompt engineering, evaluation tools, orchestration frameworks, observability platforms, and LLM API gateways. This article serves as your comprehensive guide to LLMOps. LLMOps encompasses best practices and a diverse tooling landscape.
Summary: This article provides a comprehensive guide on Big Data interview questions, covering beginner to advanced topics. This article helps aspiring candidates excel by covering the most frequently asked Big Data interview questions. Introduction Big Data continues transforming industries, making it a vital asset in 2025.
And since you are reading this article, the data scientists you support have probably reached out for help. This article is a summary of what we’ve learned from building and maintaining one of the most popular experiment trackers for the past five years. Of course, a relational database would be valuable here.
We organize all of the trending information in your field so you don't have to. Join 17,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content