Data Integration

Data Hub

Remove organizational silos

Universal connectors for your existing data sources

Beta - Q2 2024

hyperfluid.nudibranches.tech

Overview

Turn your scattered data sources into a unified analytics powerhouse. Built on Trino's distributed SQL engine and Apache Iceberg's table format, Data Hub lets you query across PostgreSQL, MongoDB, S3, and 30+ connectors as if they were one database. No more ETL headaches - just pure analytical power.

Technical Specifications

Connectors 30+ planned

SQL Engine Stateless distributed (Trino)

Storage Apache Iceberg

Cross-source Join any data source

Dataset Branching Coming 2025

Auto Optimizer Q4 2025

Use Cases

Cross-source analytics

Join PostgreSQL with MongoDB in a single query

Query any source, any format

Complex KPI computing

Advanced analytics across distributed datasets

10x faster than traditional ETL

Unified data lakehouse

All your data sources in one queryable platform

50% reduction in infrastructure costs

Hyperfluid in Action

The impossible join

5 min

Sarah needs to join customer data (PostgreSQL) with product interactions (MongoDB)

Steps

Traditional approach: Extract → Transform → Load (weeks of work)

Hyperfluid approach: One SQL query across both sources

SELECT * FROM postgres.customers JOIN mongo.interactions...

Results in seconds, without moving any data

Result

Complex analytics that used to take weeks, now in real-time

The KPI revolution

30 min

Finance team calculates monthly revenue across 8 different systems

Steps

Connect to all 8 systems via Data Hub connectors

Write one SQL query spanning all sources

Trino engine distributes computation automatically

Complex revenue calculation with proper attribution

Result

Monthly reporting from 2 weeks to 30 minutes

The data time machine

1 click

Thanks to Iceberg, travel back in time across all your data (Coming 2025)

Steps

Create dataset branch for Q3 analysis

Experiment with data transformations safely

Compare results with main branch

Merge successful changes or discard experiments

Result

Safe data experimentation without breaking production

Ready to experience these scenarios? Test Data Hub now!

Key Benefits

Query any source with standard SQL

No ETL required - analyze in place

Distributed computing for massive scale

Apache Iceberg for ACID transactions

Interested in Data Hub?

Discover how this component can transform your data architecture.

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