Data Pipeline

Connect, Transform, Deliver — Any Data

Multimodal ETL pipelines for structured, semi-structured, and unstructured data

Data Pipeline connects 50+ data sources with visual DAG orchestration and incremental sync. Ingest everything from database rows to PDFs and images through a single, unified pipeline framework.

Pipelines Built for the AI Era

50+ Pre-Built Connectors

Connect to databases, SaaS APIs, cloud storage, message queues, and file systems out of the box. Custom connectors via SDK for proprietary sources.

Visual DAG Orchestration

Design complex data flows with a drag-and-drop interface. Branch, merge, filter, and transform data with full dependency management and error handling.

Multimodal Ingestion

Process structured tables alongside PDFs, Word documents, images, and audio files. Each modality gets purpose-built parsing and extraction.

Incremental Sync & CDC

Change data capture and incremental loading keep downstream systems current without costly full refreshes. Schema drift detection prevents silent failures.

How It Works

1

Define Sources & Targets

Select from pre-built connectors or configure custom sources. Specify schemas, credentials, and sync modes in a unified interface.

2

Build Transformation Logic

Apply SQL transforms, Python scripts, or built-in functions through the visual DAG editor. Chain transformations across structured and unstructured data.

3

Schedule & Orchestrate

Set cron schedules, event triggers, or continuous streaming modes. The orchestrator handles retries, backpressure, and dependency resolution automatically.

4

Monitor & Optimize

Track throughput, latency, error rates, and data freshness in real time. Automated alerts flag pipeline issues before they reach downstream consumers.

Why Teams Choose Data Pipeline

3x

Unified Structured & Unstructured

One pipeline framework handles database tables and document files alike — no separate tools for different data types.

80%

Faster Pipeline Development

Visual DAG builder and pre-built connectors reduce pipeline creation from weeks of coding to hours of configuration.

10x

Always-Fresh Data

Incremental sync and CDC ensure downstream systems reflect source changes within minutes, not hours.

90%

Fewer Pipeline Failures

Schema drift detection, automatic retries, and dead-letter queues keep data flowing even when sources change unexpectedly.

Architecture Overview

Data Pipeline runs on a distributed task execution engine that horizontally scales across workers. Each pipeline stage runs as an isolated task with checkpointing, enabling exactly-once semantics and automatic recovery from failures.

  • Distributed task execution with horizontal auto-scaling
  • Exactly-once delivery with checkpoint-based recovery
  • Pluggable connector framework with SDK for custom sources
  • Unified processing model for batch, micro-batch, and streaming

Proof from customers

Simplify Your Data Integration

Build multimodal pipelines that connect any source to any destination — structured or unstructured — in a single visual interface.