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Brief
Prophecy

Prophecy

Prophecy enables data teams to build production-grade data pipelines visually while generating clean, reusable code, bridging the gap between low-code simplicity and code-first flexibility for Apache Spark and dbt workflows.

prophecy.ioSan Francisco, California, United StatesFounded 2021

Last updated May 11, 2026

Business Model
SaaS
Target Market
Enterprise
Employee Count
51-200
Funding
$61M
API Available
Yes
Market Position

Emerging player in the low-code data engineering platform space, competing with traditional ETL tools and modern data transformation platforms

Overview

Prophecy is a low-code data engineering platform, not an AdTech company. It provides visual development tools for building data pipelines using Apache Spark and dbt (data build tool). The platform enables data engineers, analysts, and scientists to collaborate on data transformation workflows through a drag-and-drop interface while still generating production-quality code. Prophecy targets enterprises looking to accelerate their data engineering processes and democratize data pipeline development across technical and semi-technical users. While Prophecy operates in the data infrastructure and analytics space rather than advertising technology, its platform could be used by AdTech companies for managing their data pipelines and analytics workflows. The company focuses on making data engineering more accessible and efficient through visual development while maintaining the flexibility and power of code-based approaches. Prophecy supports deployment across major cloud platforms including AWS, Azure, and Google Cloud.

Products & Features

Visual Data Pipeline Designer

Drag-and-drop interface for building Spark and dbt data pipelines without writing code

Code Generation

Automatically generates production-quality Spark and SQL code from visual designs

Git Integration

Native version control integration for collaborative development and CI/CD workflows

Data Lineage

Visual tracking of data flow and transformations across pipelines

Metadata Management

Centralized management of data assets, schemas, and pipeline metadata

Key Features
Visual development for Apache Spark and dbtAutomatic code generationGit-based version controlMulti-cloud support (AWS, Azure, GCP)Collaborative development environmentData lineage and impact analysisPipeline orchestration and schedulingInteractive data exploration
Use Cases
ETL/ELT pipeline developmentData warehouse transformationData lake processingReal-time data processingAnalytics data preparationMachine learning data pipelines
Customer Segments
Enterprise data teamsData engineersAnalytics engineersData analystsData scientists
Corporate history
  • 2021Founded
See integrations with Prophecy (6)

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