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OpenAI’s Acquisition of Rockset: A Bellwether for the Future of Real-time Enterprise Analytics and Vector Search

The release of ChatGPT marked a significant shift in how people interact with technology by introducing a conversational mode of inquiry using natural language to surface insights.

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Finding Competitive Coverage of the FSQ Places Dataset Over Road Networks Using Batch Isochrone Computations in One Tiny SQL Statement

by  B. Kaan Karamete, PhD.  Senior Director of Engineering Graph/Geospatial - Kinetica.com - Feb. 10, 2025 Figure 1 : The animation is created from the...
  • B. Kaan Karamete
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  • Chain of Thought, Developer Blog

Kinetica’s Memory-First Approach to Tiered Storage: Maximizing Speed and Efficiency

A key challenge for any database, whether distributed or not, is the constant movement of data between a hard disk and system memory (RAM). This...
  • Hari Subhash
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Migrating from Rockset to Kinetica: A How-To Guide

With Rockset being sunsetted by September 30th, many of its customers are left in the lurch, seeking a reliable alternative for their real-time data analytics...
  • Hari Subhash
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OpenAI’s Acquisition of Rockset: A Bellwether for the Future of Real-time Enterprise Analytics and Vector Search

The release of ChatGPT marked a significant shift in how people interact with technology by introducing a conversational mode of inquiry using natural language to...
  • Nima Negahban
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Preventing Cyber Attacks: How Kinetica Can Save the Energy Sector Millions of Dollars

Imagine waking up one morning to find that your local gas station has run dry, leaving you stranded without fuel. This was the harsh reality...
  • Hari Subhash
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Kinetica, the GPU-powered RAG Engine for Data Copilots, Integrates with NVIDIA NIM

Kinetica, the GPU-powered RAG (Retrieval Augmented Generation) engine, is now integrating deeply with NVIDIA Inference Microservices for embedding generation and LLM inference. This integration allows...
  • Hari Subhash
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Gen. AI Needs a Real-time Multimodal Retrieval Engine

Until recently, pure vector databases like Pinecone, Milvus, and Zilliz were all the rage. These databases emerged to meet a critical need: Large Language Models...
  • Hari Subhash
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Kinetica Confluent a match made in streaming heaven

Every moment, trillions of entities—vehicles, stock prices, drones, weather events, and beyond—are in constant motion. Imagine the vast opportunities and insights we could uncover by...
  • Hari Subhash
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Kinetica joins the Connect with Confluent Partner Program

We are thrilled to announce that Kinetica has now joined the Connect with Confluent Partner program. This collaboration merges the unparalleled speed of Kinetica's GPU-accelerated...
  • Nima Negahban
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  • Developer Blog

How to deploy natural language to SQL on your own data – in just one hour with Kinetica SQL-GPT

You’ve seen how Kinetica enables generative AI to create working SQL queries from natural-language questions, using data set up for the demonstration by Kinetica engineers. ...
  • Chad Juliano
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  • Developer Blog

The mission to make data conversational

I think one of the most important challenges for organizations today is to use the data they already have more effectively, in order to better...
  • Chad Juliano
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  • Developer Blog

Towards long-term memory recall with Kinetica, an LLM, and contexts

Prior to the emergence of machine learning, and particularly “deep learning,” I was an ML skeptic.  Judging from what I saw from the state of...
  • Chad Juliano
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  • Chain of Thought

The GPU strikes back: Why the GPU will be the premiere compute device for Analytics not just AI

Since their inception, databases had been designed with the notion of compute being a scarce resource.  So they organized data in advanced data structures, on...
  • Nima Negahban
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  • Kinetica In Motion

Where Matters: The Significance of Location in Vehicle Telemetry Data Analysis

The proliferation of sensors in automobiles has ushered in a new era of data-rich vehicles, offering immense benefits in terms of analyzing this wealth of...
  • Chad Meley
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  • Chain of Thought

Getting answers from your data now: Natural language-to-SQL

Generative AI has raised people’s expectations about how soon they can get answers to the novel questions they pose.  What amazes them first is how...
  • Nima Negahban
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  • Kinetica In Motion

The Future is a Conversation: Democratizing big data analytics with Kinetica

Every so often, there emerges a technological breakthrough that fundamentally shifts the way we interact with the world—transforming mere data points into a narrative that...
  • Nima Negahban
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  • Kinetica In Motion

True Ad-Hoc Analytics: Breaking Free from the Canned Query Constraint

Many database vendors often boast about their support for ad-hoc querying and analytics, but in practice, true ad-hoc capability remains elusive. While the term "ad-hoc"...
  • Chad Meley
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  • Kinetica In Motion

A New Tool for Large GIS Datasets

Today, many GIS users jump out of their systems and use Postgres or SQLServer to run spatial queries on larger datasets. While this is a...
  • Linda Stevens
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