Part 2: Data Integration Platforms' Initial & Resync Time Benchmark

In Part 1 of this database replication resync time benchmark study, we discussed why minimizing your database replication resync times is of upmost importance when building mission-critical data products. In this Part 2, we share the breakdown of the tests that were carried out and the detailed results for each platform. The six platforms that we benchmarked for their CDC database replication resync times were.

Unlocking Geospatial Data in Snowflake: Store, Analyze, And Visualize At Scale

Snowflake provides for seamless handling of geospatial data, making it easier to work with location-based information directly in your data platform. In this video, we explore Snowflake’s native support for geospatial data, which allows you to store, process, and analyze spatial information at scale. Geospatial data is important because everything happens somewhere. By breaking down silos and combining spatial and non-spatial data, Snowflake empowers you to uncover valuable insights across a wide range of use cases —from mapping to location analytics to geospatial trends.

Empowering Real-time Data Replication: Unleashing the Potential of Qlik Replicate and Amazon MSK

In the current data intensive world we live in many customers deal with heavy volumes of data that reside in databases and streaming systems. There are many ways to move data from one cloud platform to another, but for efficient migration, ease of use/development, and near zero downtime, a tool that does continuous near real-time data movement and CDC (change data capture) is needed.

Optimizing Supply Chains with Data Streaming and Generative AI

It’s a truism that global supply chains are complex. The process of sourcing raw materials, transforming them into finished products, and distributing them to customers encompasses numerous systems (e.g., ERPs, WMSs, and TMSs). All systems within “the supply chain” are trending in the same direction; they’re aiming to be more efficient, resilient, and agile. Various technological developments have facilitated this directional trend.

Demo | Snowflake Data Clean Rooms

Snowflake Data Clean Rooms empower organizations to collaborate on data in a privacy-conscious way directly within Snowflake. With an intuitive interface and a focus on simplifying secure data sharing, Snowflake Data Clean Rooms enables businesses to build and use clean rooms seamlessly, leveraging Snowflake’s powerful data platform. This solution eliminates unnecessary complexity and additional access fees, ensuring organizations can focus on deriving insights while maintaining data privacy. Learn more about how Snowflake Data Clean Rooms support privacy-preserving collaboration in this blog.

Benchmarking llama.cpp on Arm Neoverse-based AWS Graviton instances with ClearML

By Erez Schnaider, Technical Product Marketing Manager, ClearML In a previous blog post, we demonstrated how easy it is to leverage Arm Neoverse-based Graviton instances on AWS to run training workloads. In this post, we’ll explore how ClearML simplifies the management and deployment of LLM inference using llama.cpp on Arm-based instances and helps deliver up to 4x performance compared to x86 alternatives on AWS. (Want to run llama.cpp directly?

How to Display Charts on a Dashboard Like a Catalog

Yellowfin provide extensive customization for the design of dashboard content so you can achieve the exact look and feel required for your unique business audience and use case. Out-of-the-box, our drag-and-drop design canvas (Yellowfin Canvas) and low-code, no-code user interface enables non-developers to easily access many handy features. However, sometimes, you may want to extend Yellowfin further, or control the design and layout of your dashboard in a more specific way.

SwiftKV from Snowflake AI Research Reduces Inference Costs of Meta Llama LLMs up to 75% on Cortex AI

Large language models (LLMs) are at the heart of generative AI transformations, driving solutions across industries — from efficient customer support to simplified data analysis. Enterprises need performant, cost-effective and low-latency inference to scale their gen AI solutions. Yet, the complexity and computational demands of LLM inference present a challenge. Inference costs remain prohibitive for many workloads. That’s where SwiftKV and Snowflake Cortex AI come in.

The AI Tipping Point: What Manufacturing Leaders Need to Know for 2025

AI is proving that it’s here to stay. While 2023 brought wonder, and 2024 saw widespread experimentation, 2025 will be the year that manufacturing enterprises get serious about AI's applications. But it’s complicated: AI proofs of concept are graduating from the sandbox to production, just as some of AI’s biggest cheerleaders are turning a bit dour.