[Building Blocks] ParadeDB – Postgres for Search and Analytics (Philippe Noël)
ParadeDB is Postgres for search and analytics. It is an alternative to Elasticsearch built on Postgres. It offers state-of-the-art full-text and vector search capabilities, as well as fast aggregations inside Postgres. ParadeDB is built in Rust via Postgres extensions on top of database building blocks like Tantivy, DuckDB, and Apache DataFusion. It is compatible with every officially supported PGDG Postgres version. In this talk, we'll discuss how we extended Postgres with these building blocks and dive into the technical details... Read More
[DB Seminar] JSON Relational Duality: Converging the worlds of Objects, Documents, and Relational
The "Object-Relational Impedance Mismatch" has been a multi-decade problem for developers, and past solutions have all had various tradeoffs that have compromised efficiency or consistency. JSON Relational Duality is a breakthrough capability that combines the best aspects of the Document model and the Relational models without the drawbacks of either model. This session will provide an overview and deep dive into the inner workings of JSON Relational Duality. We will also discuss some of the benefits of being able to... Read More
[Building Blocks] Accelerating Apache Spark workloads with Apache DataFusion Comet (Andy Grove)
Apache Spark is one of the most widely-used distributed data analysis frameworks. However, its JVM-based and row-oriented query execution engine limits Spark’s performance and scalability. In this talk, we will introduce DataFusion Comet, an accelerator for Apache Spark designed to improve the efficiency of Spark queries by translating them into native queries that leverage Apache Arrow and Apache DataFusion. We will explore the core architecture of Comet and explain how Spark plans are translated into native plans and talk about... Read More
[Building Blocks] Apache Arrow DataFusion: A Fast, Embeddable, Modular Analytic Query Engine (Andrew Lamb)
Apache DataFusion is a fast, embeddable, and extensible query engine written in Rust that uses Apache Arrow as its memory model. In this talk we explain DataFusion in more detail and describe the types of data centric systems it is used to build. We will also review its high level architecture and feature set, discussing tradeoffs and performance between DataFusion's modularity vs more common tightly coupled design. This talk is part of the Database Building Blocks Seminar Series. Zoom Link:... Read More
Industry Affiliates Program Visit 2024 – Day 2
The second day of Carnegie Mellon University's Database Industry Affiliate Program (IAP) Visit Day, held in the Gates-Hillman Center, shifts focus to the industry side, featuring a series of informative sessions presented by member companies. These sessions offer companies the opportunity to showcase their latest innovations, products, and challenges in the database space, while also highlighting potential career opportunities for students. Attendees, including faculty, students, and other participants, can engage directly with company representatives to learn about real-world applications of... Read More
Industry Affiliates Program Visit 2024 – Day 1
The first day of Carnegie Mellon University's Database Industry Affiliate Program (IAP) Visit Day takes place in the Gates-Hillman Center and is focused on showcasing cutting-edge research in the field of databases. The day is filled with a series of research talks delivered by faculty and students from the university's database group. These presentations provide an in-depth look at the latest advancements in database technologies, methodologies, and applications. Attendees, including industry partners, gain valuable insights into innovative projects, ongoing research,... Read More
[Fall 2024] Advancing Database Performance and Capabilities at Snowflake
This talk presents recent research and development at Snowflake aimed at pushing the boundaries of database performance and functionality. In the first section, we will introduce a series of optimizations designed to accelerate query execution within Snowflake’s platform. We will discuss the technical challenges associated with developing general-purpose optimizations and balancing performance improvements across a wide range of workloads. The second section will explore a novel database constraint we’re developing to enable continuous processing applications. A finalization constraint restricts the... Read More
[Fall 2024] Databricks: Introduction to Mosaic AI Vector Search
This tech talk will deep dive into some of the most interesting challenges being solved at Databricks. Read More
LSM Management and Using LSM Immutability for Data Virtualization (Vaibhav Arora)
LSM (Log-Structured Merge) trees are now the bedrock of many storage engines and datastores like RocksDB, HBase, Cassandra etc. They provide the ability to avoid random-writes, and provide immutability. Data is organized in multiple-levels that are exponentially increasing in size. Each data mutation writes a new version of an object, and background processes named merge/compaction continuously remove the unused versions, while moving the data across the layers of the LSM tree and maintain its shape. This talk will describe how... Read More
Leveraging Generative AI with Oracle AI Vector Search (Shasank Chavan)
AI Vector Search in Oracle 23ai is a new, transformative way to intelligently search through your unstructured business data efficiently, and accurately, by using AI techniques to match on the semantics, or meaning, of the underlying data. With the inclusion of a new VECTOR datatype, new approximate search indexes, and new SQL operators and extensions, enterprise companies can quickly and easily leverage AI Vector Search to build modern, generative-ai applications with just a few lines of SQL! And with this... Read More