Datafold Analysis: $20M Raised

• Customized pricing based on the number of users and tables being monitored and tested.
• Comprehensive platform generally purchased by data teams.
• Specific features like one-time migration conversion and validation or column-level lineage can be purchased separately.

224 W 35th St #500, New York City, New York 10001, United States

Datafold primarily focuses on the data quality and data management industry, providing solutions for data testing, monitoring, and ensuring data accuracy throughout workflows.

• New Enterprise Associates (NEA)
• Amplify Partners
• Y Combinator
• Angel Collective Opportunity Fund

Datafold has raised a total of $22.1 million over three funding rounds, with these investors participating in their Series A round and earlier seed funding.

Datafold operates in the data quality and observability market, facing competition from several notable companies. The main competitors include:

1. Bigeye: Specializes in data observability with automated data quality monitoring and anomaly detection, helping organizations maintain data integrity.

2. Databand: Offers a comprehensive data observability platform that assists data engineers in identifying and fixing data quality issues, emphasizing operational efficiency and broader integration with various data platforms.

3. Monte Carlo: Focuses on preventing data downtime and ensuring visibility across data tools, particularly in sectors like financial services and healthcare. It is noted for its end-to-end solution for broken data pipelines.

4. Metaplane: Provides features like data lineage visualization, real-time monitoring, and rule-based validation. It is recognized for its intuitive user interface and scalability but has a steeper learning curve compared to Datafold.

5. Hightouch: Known for its user-friendly interface, it allows users to sync customer data into various tools without engineering support, making it more accessible than Datafold.

6. Census: Offers a platform for syncing data from warehouses to business applications, praised for its ease of setup and administration.

7. Validio: Focuses on data governance and quality, automating anomaly detection and lineage mapping.

Notable differences include the specific features and target industries of each competitor. For instance, while Bigeye emphasizes automated monitoring, Databand is more focused on troubleshooting and operational fixes. Monte Carlo provides broader interoperability between various data tools, appealing to organizations with complex data ecosystems.