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.

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Unveiling Spark's Core: A Deep Dive into its Execution and Optimization Engine

on May 6, 2026

Apache Spark has become the de-facto standard for large-scale data processing, analytics, and machine learning. While many interact with its intuitive APIs, a true mastery of Spark, and the ability to diagnose and optimize complex workloads, hinges on understanding its “under-the-hood” mechanics. This deep dive will pull back the curtain, exploring Spark’s architectural patterns, its sophisticated optimization engine, and critical aspects like shuffle management and fault tolerance. The Anatomy of a Spark Application Every Spark application runs as a set of independent processes on a cluster, coordinated by the SparkContext in the driver program.

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Hermes Agent Unveiled: Architectural Deep Dive for Robust Data Telemetry

on May 3, 2026

The landscape of distributed systems demands robust and efficient telemetry collection. While many agents exist, the Hermes Agent distinguishes itself with a lightweight footprint, modular design, and a strong emphasis on reliability and security. This deep dive moves beyond a generic overview, peeling back the layers to explore Hermes Agent’s “under-the-hood” architecture, configuration patterns, and practical implementation challenges within the DataFibers ecosystem. The Hermes Philosophy: Input, Process, Output At its core, Hermes Agent operates on a simple, yet powerful, pipeline: Input sources data, Processors transform and filter it, and Outputs deliver it to various destinations.

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Beyond Basics: Architecting Robust RAG Pipelines for LLMs

on April 29, 2026

The rise of Large Language Models (LLMs) has revolutionized how we interact with information. However, their inherent limitations—hallucinations, outdated knowledge, and lack of domain-specific context—often hinder their utility in enterprise applications. This is where Retrieval Augmented Generation (RAG) shines. Instead of a generic overview, this deep-dive explores the intricate architecture and critical engineering considerations required to build truly robust and performant RAG pipelines. The Fundamental Challenge: Bridging LLM Gaps LLMs excel at linguistic tasks, but their knowledge is frozen at their last training cutoff.

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Databricks Under the Hood: Dissecting the Lakehouse Engine for Performance and Governance

on April 26, 2026

Databricks Under the Hood: Dissecting the Lakehouse Engine for Performance and Governance Databricks has established itself as a cornerstone of modern data architectures, unifying data warehousing and data lakes into the powerful “Lakehouse” paradigm. But beyond the marketing and high-level promises, what truly powers Databricks? How does it deliver on its guarantees of performance, reliability, and governance? This deep dive will pull back the curtain, exploring its core architecture, underlying technologies, and practical operational patterns.

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