[Building Blocks] Towards “Unified” Compute Engines: Opportunities and Challenges (Mehmet Ozan Kabak)

Speaker:

Mehmet Ozan Kabak

System:

Synnada

Video:

YouTube

The architecture diagram of a typical data and AI infrastructure setup often features a primary compute engine (e.g., Apache Spark) alongside an array of supplementary tools for observability, AI integration, streaming support, memory management, interactivity, and more. While this modular architecture can be effective, it also introduces challenges around performance bottlenecks, maintenance costs, and integration complexity. In this talk, we... Read More

[Building Blocks] Exon: A Built for Purpose Bioinformatics Database (Trent Hauck)

Speaker:

Trent Hauck

System:

Exon

Video:

YouTube

Without having to implement every component of a database engine, it’s now feasible to build databases that can lean into the idiosyncrasies of specific domains to deliver a better user experience. Exon is one such databases. Thanks to DataFusion, Exon can deliver a complete database, but also have capabilities bridge the gap between bioinformatics and database systems. In this talk... Read More

[Building Blocks] Accelerating Data and AI with Spice.ai Open-Source Software (Luke Kim)

Speaker:

Luke Kim

System:

Spice.ai

Video:

YouTube

Spice.ai OSS is an open-source, portable runtime designed to simplify building data and AI applications. It’s built on industry leading technologies like Apache DataFusion, Apache Arrow, DuckDB and SQLite. In this talk, we tell the story of building neurofeedback systems, to operating DuckDB at cloud-scale, to building Spice.ai OSS for the intersection of high-performance data query and ML-inference. We introduce... Read More

[Building Blocks] ParadeDB – Postgres for Search and Analytics (Philippe Noël)

Speaker:

Philippe Noël

System:

ParadeDB

Video:

YouTube

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... Read More

[DB Seminar] JSON Relational Duality: Converging the worlds of Objects, Documents, and Relational

Speaker:

Tirthankar Lahiri

System:

Oracle

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... Read More

[Building Blocks] Accelerating Apache Spark workloads with Apache DataFusion Comet (Andy Grove)

Speaker:

Andy Grove

System:

DataFusion

Video:

YouTube

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... Read More

[Building Blocks] Apache Arrow DataFusion: A Fast, Embeddable, Modular Analytic Query Engine (Andrew Lamb)

Speaker:

Andrew Lamb

System:

DataFusion

Video:

YouTube

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... 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... 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... Read More

[Fall 2024] Advancing Database Performance and Capabilities at Snowflake

Speakers:

Dan Sotolongo, Bowei Chen

System:

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... Read More