Media Summary: While many teams attempt to build AI agent memory through basic LLM prompts and traditional databases, they often miss 75% of ... Co-founder and CEO of Neon, Nikita Shamgunov shares how production AI needs a new kind of database Introducing LTAP: the first Lake Transactional/Analytical Processing

Databricks Lakebase Architecture The Serverless - Detailed Analysis & Overview

While many teams attempt to build AI agent memory through basic LLM prompts and traditional databases, they often miss 75% of ... Co-founder and CEO of Neon, Nikita Shamgunov shares how production AI needs a new kind of database Introducing LTAP: the first Lake Transactional/Analytical Processing As we venture into the future of data engineering, streaming and Apache Kafka in conjunction with Apache Spark became the de facto standard for processing and analyzing data.

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Databricks Lakebase Architecture -The Serverless Postgres Revolution
Introducing Lakebase - Databricks Co-founder & Chief Architect Reynold Xin
Introduction to Lakebase: OLTP for Data Apps and AI Agents
AI Agents That Remember: Building Stateful Systems with Lakebase
Lakebase - OLTP Workloads on Databricks!
A New Kind of Database Architecture with Nikita Shamgunov, Co-founder and CEO of Neon
BrickTalks: Lakebase Autoscaling Deep Dive: How to OLTP with Databricks
Introducing LTAP (Lake Transactional/Analytical Processing): a new data processing architecture
Embracing the Future of Data Engineering: The Serverless, Real-Time Lakehouse in Action
Databricks Lakebase & Lakehouse Explained: OLTP Meets OLAP
Lakebase Explained in 2 minutess | Why This Databricks Update Matters
What Is Databricks Lakebase? The New Database for AI Agents
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Databricks Lakebase Architecture -The Serverless Postgres Revolution

Databricks Lakebase Architecture -The Serverless Postgres Revolution

Databricks Lakebase

Introducing Lakebase - Databricks Co-founder & Chief Architect Reynold Xin

Introducing Lakebase - Databricks Co-founder & Chief Architect Reynold Xin

Introducing

Introduction to Lakebase: OLTP for Data Apps and AI Agents

Introduction to Lakebase: OLTP for Data Apps and AI Agents

In this video, you will learn how

AI Agents That Remember: Building Stateful Systems with Lakebase

AI Agents That Remember: Building Stateful Systems with Lakebase

While many teams attempt to build AI agent memory through basic LLM prompts and traditional databases, they often miss 75% of ...

Lakebase - OLTP Workloads on Databricks!

Lakebase - OLTP Workloads on Databricks!

Curious how

A New Kind of Database Architecture with Nikita Shamgunov, Co-founder and CEO of Neon

A New Kind of Database Architecture with Nikita Shamgunov, Co-founder and CEO of Neon

Co-founder and CEO of Neon, Nikita Shamgunov shares how production AI needs a new kind of database

BrickTalks: Lakebase Autoscaling Deep Dive: How to OLTP with Databricks

BrickTalks: Lakebase Autoscaling Deep Dive: How to OLTP with Databricks

Discover the power of

Introducing LTAP (Lake Transactional/Analytical Processing): a new data processing architecture

Introducing LTAP (Lake Transactional/Analytical Processing): a new data processing architecture

Introducing LTAP: the first Lake Transactional/Analytical Processing

Embracing the Future of Data Engineering: The Serverless, Real-Time Lakehouse in Action

Embracing the Future of Data Engineering: The Serverless, Real-Time Lakehouse in Action

As we venture into the future of data engineering, streaming and

Databricks Lakebase & Lakehouse Explained: OLTP Meets OLAP

Databricks Lakebase & Lakehouse Explained: OLTP Meets OLAP

Confused about

Lakebase Explained in 2 minutess | Why This Databricks Update Matters

Lakebase Explained in 2 minutess | Why This Databricks Update Matters

Lakebase

What Is Databricks Lakebase? The New Database for AI Agents

What Is Databricks Lakebase? The New Database for AI Agents

We're onboarding

Serverless Kafka and Apache Spark in a Multi-Cloud Data Lakehouse Architecture

Serverless Kafka and Apache Spark in a Multi-Cloud Data Lakehouse Architecture

Apache Kafka in conjunction with Apache Spark became the de facto standard for processing and analyzing data.