Datacoral
Acquired by ClouderaAutomated serverless data infrastructure that eliminates the operational complexity of building and maintaining data pipelines, enabling data teams to focus on analytics rather than infrastructure management.
Last updated Feb 8, 2026
- Industry
- Data Infrastructure
- Business Model
- SaaS
- Target Market
- Mid-Market, Enterprise
- Employee Count
- 11-50
- Funding
- $10M
- Parent Company
- Cloudera
- API Available
- Yes
Market Position
Niche player in serverless data pipeline automation, acquired by Cloudera in 2020
Overview
Datacoral was a serverless data infrastructure platform founded to automate and simplify the entire data lifecycle for modern businesses. The company provided a managed data pipeline solution that handled data ingestion, transformation, orchestration, and monitoring, built on top of AWS infrastructure. While not strictly an AdTech company, Datacoral served the broader data infrastructure market that includes AdTech companies needing to process and analyze large volumes of advertising and customer data. The platform was designed to eliminate the operational overhead of building and maintaining data pipelines, allowing data teams to focus on analytics rather than infrastructure management. In 2020, Datacoral was acquired by Cloudera, a major enterprise data platform company, and its technology was integrated into Cloudera's DataFlow offerings. The acquisition reflected the growing importance of automated, cloud-native data pipeline solutions in the enterprise data management landscape.
Products & Features
Data Pipeline Engine
Serverless orchestration engine for automating data workflows from ingestion to transformation
Pre-built Connectors
Library of connectors for common data sources and destinations including databases, data warehouses, and SaaS applications
Data Monitoring
Built-in monitoring and alerting for data quality, pipeline health, and operational metrics
Data Catalog
Automated data discovery and cataloging for improved data governance and lineage tracking
Key Features
Serverless architecture on AWSAutomated data pipeline orchestrationPre-built data connectorsData quality monitoringSQL-based transformationsAutomatic schema detectionData lineage trackingInfrastructure as code
Use Cases
Centralizing data from multiple sources into data warehousesBuilding automated ETL/ELT pipelinesReal-time data ingestion and processingData lake construction and managementAnalytics data preparationMarketing and advertising data consolidation
Customer Segments
Data-driven enterprisesE-commerce companiesSaaS companiesDigital marketing agenciesFinancial servicesTechnology companies