Shift-left analytics brings analytical processes to the start of the data lifecycle, similar to the shift-left model for data products using tools like Apache Flink. This approach focuses on gaining insights during initial data ingestion and processing, rather than after full processing or storage.

In a traditional analytics workflow, teams often wait un…

What is an Agent?

An AI agent is an autonomous system that performs tasks on behalf of a user or system. These agents range from simple chatbots to advanced decision-making systems, making them essential in modern AI applications.

What is an Agent Mesh?

AI agent mesh is the  orchestration and coordination of multiple autonomous agents, allowing them to col…

A "stream house" concept refers to integrating streaming platforms with lakehouse architectures. If Confluent were to implement a stream house, it would likely involve the seamless combination of streaming data processing with the capabilities of a lakehouse, allowing for efficient data storage and retrieval using open table formats like Apache Iceberg.

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Apache Pinot is a great choice of real-time analytics platform for organizations looking to process and analyze large datasets in real-time more efficiently. Data sketches are a capability that allows Pinot to enhance query speed and performance. In this blog, I’ll introduce the concept of data sketches, how they’re used in Apache Pinot, and the benefit…

Confluent recently announced its acquisition of WarpStream, an innovative Kafka-compatible streaming solution designed with a unique architecture. This acquisition aims to enhance Confluent's offerings by adding a cloud-native streaming solution that can be deployed in customers' own cloud accounts.

Jay Kreps, the CEO and co-founder of Confluent, express…

Recently, there has been a lot of talk in AI circles about the term "agentic." When we refer to AI systems as "agentic" or "agents," we highlight their capacity to act autonomously and proactively, much like a human agent would. An agentic AI system can make decisions, take actions, and engage with its surroundings independently, aiming to accomplish se…

Building a strong foundation for data analytics is crucial for organizations seeking to derive valuable insights and make informed decisions. In this blog post, we explore how to establish a structured data model that instills confidence and trust in the analytics derived from the system. By delving into key components, we uncover the importance of line…

When you work with data, you need a way to retrieve that data. When you’re done processing said data, you need to save it. Connectors do the job of sourcing and sinking data you or your application uses.

In a simple data pipeline:

source → process → sink

In this simple example, I already have two connectors. Even if the source and sink are the same syste…

At RTA Summit 2024, we will have a booth demonstration showcasing Apache Pinot’s ability to serve analytics and similarity search in real-time. There is actually a lot to make this successful. Let me unpack this by describing the use case.

At conferences, you should always have someone at your booth to answer questions, hand out swag, and …