Planet MySQL HA Blog

The Planet MySQL HA Blog aggregates content from sources that cover topics related to high availability (HA) for MySQL databases.

MySQL Basics: Turning the Page—Using LIMIT and OFFSET for Pagination

Discover how to tame big tables using LIMIT and OFFSET in MySQL! This post makes pagination easy for newcomers, using friendly library metaphors, step-by-step SQL examples, and practical tips to help you view your data one page at a time.

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Removing the index guesstimate with MySQL Autopilot Indexing

This blog post introduces the MySQL Autopilot Indexing feature.

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Interact with MySQL in natural language

We are excited to announce the release of Natural Language to SQL (NL2SQL) capability for MySQL (with the AI option) and MySQL HeatWave cloud service. Natural language interface is essential for modern data platforms, allowing users to explore information more quickly.

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Build a Smart Weather Agent with LangChain and MySQL HeatWave GenAI

Agentic AI represents a significant leap forward from simple chatbots. Instead of just responding to a single question, an AI “agent” can proactively pursue a goal. It can decompose a complex request into a logical series of steps, choose the right tools for each step—like querying a database or running a calculation—and then execute that […]

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Build a Smart Weather Agent with LangChain and MySQL HeatWave GenAI

This article showcases the power of combining the LangChain framework with an LLM hosted on MySQL HeatWave GenAI. Our goal is to create an agent that can answer the question, "What is the current weather in Fahrenheit?". To do this, the agent must first fetch the weather (which is in Celsius) and then convert it to Fahrenheit, a classic multi-step task. This agent will demonstrate how a Large Language Model (LLM) can use tools and a logical sequence of steps to solve a problem.

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Build a RAG System with LangChain and MySQL HeatWave GenAI

Retrieval-Augmented Generation (RAG) is a powerful technique that enhances the capabilities of Large Language Models (LLMs) for enterprise data. By grounding the model in information from your vector store/knowledge base, RAG helps produce more accurate, relevant, and trustworthy answers. MySQL HeatWave is a fully managed MySQL database service that combines transactions, analytics, machine learning, and […]

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Build a RAG System with LangChain and MySQL HeatWave GenAI

This post will guide you through building a simple RAG workflow using the popular LangChain framework, powered entirely by the in-database AI capabilities of MySQL HeatWave GenAI. We will ingest a public blog post, index it in the HeatWave Vector Store, and use a HeatWave-hosted LLM to answer questions based on its content following the LangChain guide to creating vector stores and using them for RAG.

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Streamlining GenAI and ML Application Development with the MySQL HeatWave Python SDK

Introduction MySQL HeatWave is a fully managed MySQL database service that combines transactions, analytics, machine learning, and GenAI services, without ETL duplication. Also included is MySQL HeatWave Lakehouse, which allows users to query data in object storage, MySQL databases, or a combination of both. Users can deploy MySQL HeatWave–powered apps on a choice of public […]

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Semantic and Keyword—Hybrid Search in MySQL HeatWave

Introduction MySQL HeatWave is a fully managed MySQL database service that combines transactions, analytics, machine learning, and GenAI services, without ETL duplication. Also included is MySQL HeatWave Lakehouse, which allows users to query data in object storage, MySQL databases, or a combination of both. Users can deploy MySQL HeatWave–powered apps on a choice of public […]

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Introducing Delta Lake in MySQL HeatWave Lakehouse

MySQL HeatWave Lakehouse enables queries on file formats like Parquet, Avro, ND-JSON and CSV in an object store. This blog introduces support for the Delta Lake table format, thereby enabling ACID-compliant applications on data in the object store. Introduction Delta Lake is an open-table format built for data lake environments. It stores data in Parquet […]

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