An Open Source Big Data Bus

The goal of DataFibers is
to simplify big data processing
and be your Data Heros

Simple, but Powerful

  • Various data connects and sinks
  • Stream and Batch trasnforms
  • Topics, Schema and Meta-data
  • Data enginering and science together

Complete Guideline

  • The Insignt of Big data processing
  • The value of Kappa architecture
  • Considerations of design
  • Best practice with DataFibers
  • Rest API Document

Services

  • Community Support
  • Professional Support
  • Consulting Service
  • Technical trainings
  • Meetup and Conference

Simple

Simply build, plug, and immediately subscribe your data anywhere at anytime.

FLEXIBLE

Batch, Stream, Real-Time, or Hybrid data processing are right at hand.

Powerful

Data landing, discovery, transfer, transform, cache, mining are all in one place.

Consulting

Explore the oppotunities from DataFibers and Big Data to business success

Support

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

Training

We have provided on-line and off-line big data professional trainings across world.

Know more about DataFibers?

Check out <<DataFibers Complete Guideline>>

Read Our EBook

From our blog

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

Read more

Beyond Autocomplete: An Under-the-Hood Look at OpenAI Codex for AI Engineers

on November 11, 2026

The world of software development has been irrevocably changed by Large Language Models (LLMs). While many are familiar with general-purpose LLMs for text generation, OpenAI’s Codex stands out as a specialized marvel, engineered specifically to understand and generate code. Far from being a mere autocomplete tool, Codex represents a sophisticated synthesis of deep learning and domain-specific knowledge. This deep dive will peel back the layers, exploring Codex’s architectural underpinnings, specialized training methodologies, and practical implications for AI engineers.

Continue reading

Read more

DeepSeek Under the Hood: Dissecting MoE Architectures and Practical Deployment

on November 8, 2026

Large Language Models (LLMs) have taken the world by storm, but their sheer size often presents significant challenges in terms of training, inference, and cost. Enter DeepSeek, a family of powerful models that brings innovation through architectural choices, particularly the Mixture-of-Experts (MoE) paradigm in DeepSeek-V2 and specialized training for DeepSeek-Coder. This deep-dive explores the ‘how’ and ‘why’ behind DeepSeek’s efficiency and capabilities, moving beyond surface-level benchmarks to the nitty-gritty of its architecture and practical deployment.

Continue reading

Read more

Beyond the Basics: Demystifying Azure Networking for Secure Interconnections

on October 28, 2026

In the sprawling landscape of cloud computing, networking isn’t just a configuration step; it’s the fundamental backbone defining the security, performance, and scalability of your entire infrastructure. While Azure provides intuitive interfaces for spinning up Virtual Networks (VNets), truly mastering Azure networking demands a deep dive into its underlying mechanisms, architectural patterns, and the practical challenges of building robust, interconnected systems. This post goes beyond generic overviews. We’ll peel back the layers to understand how Azure’s networking constructs truly operate, explore critical inter-VNet communication, and delve into private connectivity options, all illuminated with code, CLI commands, and architectural diagrams.

Continue reading

Read more

Unpacking RAG: An Under-the-Hood Deep Dive into Retrieval Augmented Generation Architectures

on October 21, 2026

The promise of Large Language Models (LLMs) is transformative, yet their Achilles’ heel often lies in their knowledge cutoff and propensity for ‘hallucinations.’ Retrieval Augmented Generation (RAG) emerged as a powerful paradigm to address these limitations, grounding LLM responses in factual, external knowledge. But beyond the high-level concept of ‘retrieving and generating,’ what does a robust, production-ready RAG system truly entail? This deep dive will pull back the curtain, exploring the architectural nuances, core components, and common challenges in building sophisticated RAG applications.

Continue reading

Our Technologies