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We actively support development/deployment requests on DataFibers and queries on big data use cases.

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From our blog

Here, we are sharing our experience and best practice of using DataFibers as well as other big data technology.

Godot's Core: Unpacking the Node-Based Architecture and C++ Extensibility

on September 16, 2026

Godot’s Core: Unpacking the Node-Based Architecture and C++ Extensibility Godot Engine has rapidly ascended as a prominent open-source game development platform, celebrated for its intuitive editor and expressive scripting language. While its user-friendliness is often highlighted, a true understanding of Godot’s power lies beneath the surface – in its elegant architectural patterns, efficient resource management, and robust extensibility mechanisms. This deep dive will pull back the curtain, exploring the “how” and “why” behind Godot’s design choices, from its fundamental scene tree to its C++ module system.

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Gemini Under the Hood: Architectural Nuances for Practical Implementation

on September 6, 2026

Gemini, Google’s family of powerful, multimodal AI models, has redefined what’s possible in generative AI. Beyond the impressive demos and high-level capabilities, understanding its underlying architecture and practical interaction patterns is crucial for developers and data scientists looking to leverage its full potential. This deep dive moves beyond marketing claims to explore Gemini’s core components, how it handles multimodality, and key considerations for implementation. The Multimodal Transformer Core: A Unified Latent Space At its heart, Gemini is a sophisticated Transformer architecture.

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Databricks Under the Hood: Delta Lake, Photon, and Unity Catalog Deconstructed

on September 2, 2026

Databricks has revolutionized the data landscape, providing a unified platform for data engineering, machine learning, and analytics. While its user-friendly interface and managed Spark capabilities are well-known, the true power lies in its meticulously engineered core components. This deep dive aims to peel back the layers, exploring the architectural nuances, practical challenges, and ‘under-the-hood’ mechanisms of Databricks’ foundational technologies: Delta Lake, Photon Engine, and Unity Catalog. At the heart of Databricks’ vision for the Lakehouse is a sophisticated interplay of these systems, each addressing critical aspects of data reliability, performance, and governance.

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Beyond the Notebook: A Deep Dive into Databricks' Lakehouse Architecture and Photon Engine

on August 30, 2026

Databricks has become synonymous with the Lakehouse, democratizing data engineering, ML, and analytics. But what truly makes it tick beneath the surface? This isn’t another ‘getting started’ guide. We’re peeling back the layers to explore the architectural bedrock, the performance-boosting engines, and the practical challenges of building robust data solutions on Databricks.\n\n## Understanding the Databricks Lakehouse Architecture\nAt its core, the Databricks Lakehouse Platform unifies data warehousing and data lakes, built upon the open-source Delta Lake storage layer.

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