Databricks democratizes insights to everyone in an organization. Built on an open lakehouse architecture, the Data + AI Platform provides a unified foundation for all data and governance, combined with AI models tuned to an organization's unique characteristics. Now, anyone in an organization can benefit from automation and natural language to discover and use data like experts, and technical teams can easily build and deploy secure data and AI apps and products.

With origins in academia and the open source community, Databricks was founded in 2013 by the original creators of the lakehouse architecture and open source projects Apache Spark™, Delta Lake, MLflow and Unity Catalog.

MotherDuck makes analytics fun, frictionless, and ducking awesome. In partnership with the team building open-source database DuckDB, MotherDuck was founded by former leaders at some of the most innovative companies in data. It is on a mission to combine the elegance and speed of DuckDB with the collaboration and scalability of the cloud to provide a serverless, easy-to-use analytics platform for data small and large.

Hosted by Matthew Housley and Tony Baer, It's About Data is the topical, straight-talking podcast about data, AI, analytics "and whatever else we feel like talking about." With episodes running 15-20 minutes, we get straight to the point. Reformed data scientist Matt Housley and veteran industry analyst Tony Baer - often joined by guests from the data community - deliver their takes on current ideas, trends, vendor strategies, and technology developments impacting the data world. Episodes range from the topical (the "Snowbricks" rivalry between Databricks and Snowflake) to the strategic (the implications of MCP for agentic AI). Regularly scheduled episodes debut on YouTube, LinkedIn and Spotify every Wednesday at noon ET, but we also interrupt this program to broadcast special episodes when major headlines break.

Numeract is a Dallas-based data science firm founded by Dr. Mike Badescu, driven by the philosophy that excellence in data analysis requires both rigorous scientific methods and artistic problem-solving approaches. Their commitment to "separating signal from noise" drives their approach to transforming complex datasets into actionable insights.

Numeract specializes in developing custom data science solutions that enable organizations to extract meaningful insights from complex datasets. Numeract's expertise spans multiple technology stacks including R, Python, SQL, Docker, and Spark - covering everything from small to big data applications, research to production environments, and data processing to visualization.

Numeract's contributions to the open-source community include several R packages hosted on GitHub and CRAN, including Nmisc, which provides utilities for debugging, vector operations, and UTC date/time functionality that enhance workflows built with popular tools like dplyr and purrr. Numeract has also developed tools for AWS Lambda integration with R and flexible R pipelines with caching capabilities, demonstrating their commitment to advancing data science infrastructure.

With expertise spanning from small-scale analysis to big data implementations, research to production environments, and everything in between, Numeract excels at rapid prototyping while exploring cutting-edge technologies like deep learning with TensorFlow - to build accurate, reliable models that power data products and drive business decisions. Visit them at Numeract.com.

Franz Inc. is an early innovator in Artificial Intelligence (AI) and leading supplier of Semantic Graph Database technology with expert knowledge in developing and deploying complex Cognitive Computing solutions. AllegroGraph, Franz's flagship, high-performance, transactional, and scalable Semantic Graph Database, provides the solid storage layer for enterprise-grade NoSQL solutions. Franz's Cognitive Computing capabilities provide a powerful means to aggregate and analyze data about individual and organizational behaviors, preferences, relationships, plus spatial and temporal linkages between individuals and groups.

Tom Sawyer is the leading provider of software and services that enable organizations to build scalable and dynamic graph and data visualization and analysis applications. Customers such as AIRBUS, Cisco Systems, Equifax, IBM, JPL, Lockheed Martin, NASA, Siemens, and Toyota use our software to automatically discover and graph hidden patterns and complex relationships. We serve clients with needs in geospatial intelligence, link analysis, network topology, maps, architectures and models. We also federate data from large, diverse sources such as Neo4j, Oracle, and others. Visit tomsawyer.com to see live demonstrations.

G.V( ) helps graph database developers get s#!t done. As an all-in-one graph database IDE, G.V() helps you write, execute, and test queries; track your data model; explore and edit your graph data on the fly; and show your work with a variety of data visualizations. Compatible with 18 different graph technologies and growing, G.V() is easy to use, low cost, low commitment, vendor agnostic, and plays well with any security architecture. Amp up your productivity and get back to building cool stuff: Try out G.V() for yourself today and start querying your db in less than 5 minutes: G.V( ).

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PuppyGraph is bringing simplicity to graph analysis. With an overwhelming number of tables and complex relationships hidden within traditional databases, it's easy to feel lost. That's where the beauty of graph technology comes in - it's a simple yet powerful way to visualize and understand the intricate web of data relationships. At PuppyGraph, we understand the value of graph data analysis and the hesitation that comes with adding another layer to your tech stack. The thought of juggling additional complexity, along with the fear of spiraling costs and maintenance headaches, can be daunting. That's why we're here.

PuppyGraph was born from a vision to make graph analysis accessible and seamless for every data team, without the burdens of extra cost or complexity. Imagine being able to plug graph capabilities directly into your existing data architecture, lighting up new insights with minimal effort. That's the possibility we're turning into reality.

Streamkap is the modern real-time data exchange platform that transforms how businesses move and process data. Built on Apache Kafka and Flink, Streamkap provides streaming ETL and change data capture (CDC) with sub-second latency, enabling companies to sync data between systems in real time without the complexity of managing streaming infrastructure. The platform supports a broad range of database sources including PostgreSQL, MySQL, MongoDB, and SQL Server, seamlessly connecting to destinations like Snowflake, BigQuery, Databricks, and Redshift. With features like automated schema handling, in-stream transformations, and comprehensive security compliance (SOC 2 Type 2, GDPR/CCPA), Streamkap offers a low-maintenance solution that typically delivers 50x lower latency and 3-5x lower costs compared to traditional batch ETL tools. Founded in 2022 by data entrepreneurs Paul Dudley and Ricky Thomas, Streamkap helps businesses deliver exceptional customer experiences through real-time data that powers immediate, seamless interactions across finance, e-commerce, healthcare, and entertainment sectors.