On HPCC Systems Platform. Q&A with Richard Taylor
Q1. What is the difference between a “Data Lake” and “Data Warehouse”? A Data Lake contains raw data in its original form. That raw data is Extracted from the lake, Loaded into working...
Operational Database Management Systems
Q1. What is the difference between a “Data Lake” and “Data Warehouse”? A Data Lake contains raw data in its original form. That raw data is Extracted from the lake, Loaded into working...
Q1. You called your recent product launch ‘SingleStore Pro Max’… Talk to us about why you chose this name? In the 2000s, smartphones emerged. They eliminated the complexity of having to lug around multiple...
As an engineering leader at multiple SaaS companies, I have seen firsthand the benefits of effectively integrating data science and machine learning (ML) into our operational processes. Q1. You are Vice President of Engineering...
Time Series Database Systems (TSDBs) are specialized database systems designed to efficiently manage high-frequencytime series data. Unlike relational database systems, TSDBs rely on the general assumption that queries do not target individual tuples but summarized entries in a time...
” A data fabric is an architectural pattern that strives to create consistency among all data and metadata in an organization to make data easy to find, access, and use. A data fabric can be a...
Growing up on a farm influenced my passion for science and ultimate career path. I’m a scientist at heart and have always liked data and facts and being objective. Great science is what motivates...
by Lalit Ahuja. Generative AI “The massive adoption of freely available LLMs and the use of ChatGPT will quickly give way to enterprises enforcing their own constraints on the use of such technology, as...
Q1. What were in your opinion the main trends for the database in 2023? At the end of 2022 and the beginning of 2023, I noticed several interesting trends happening in the database ecosystem....
Q1. From a database perspective, what are the main challenges that Generative AI (GenAI) poses? The biggest challenge that Gen AI poses is scale. We have so many sources of data – data used...
Q1. What is Retrieval Augmented Generation (RAG)? Retrieval Augmented Generation (RAG) is a method that combines the capabilities of generative models, like LLMs, with information retrieval techniques. In a RAG system, when presented with...