Hevo Data vs Dagster
Side-by-side comparison of AI visibility scores, market position, and capabilities
No-code data pipeline and real-time ELT platform; San Francisco/Bengaluru; raised $42M+ from Sequoia India; supports 150+ data sources;
About
Hevo Data is a no-code data pipeline and real-time ELT platform founded in 2017 and headquartered in San Francisco, California, with core engineering in Bengaluru, India. The company was founded by Manish Jethani and Sourabh Agarwal to provide a simpler alternative to complex, code-heavy data pipeline tools for data teams that do not have dedicated data engineering resources. Hevo's platform enables analysts and non-engineers to connect data sources, define transformations using a visual interface or Python, and load data into cloud data warehouses without writing connector code or managing pipeline infrastructure.\n\nHevo raised $42 million in funding from investors including Sequoia Capital India, Qualgro, and Unusual Ventures. The platform supports more than 150 data sources including databases, SaaS applications, advertising platforms, payment processors, and custom webhooks. Its real-time data pipeline engine processes and delivers data with sub-minute latency for streaming sources, making it suitable for analytics use cases that require near-real-time freshness. Hevo's automatic schema management handles changes in source schemas without pipeline failures, addressing one of the most common maintenance burdens for data teams.\n\nHevo positions itself as a cost-effective alternative to Fivetran and Stitch for mid-market companies and growing data teams that need broader connector coverage at lower price points. The platform's transformation capabilities include a visual mapping interface for simple field transformations, a Python transformer for complex data manipulation, and dbt integration for warehouse-native transformations. Hevo is particularly popular in the Asia-Pacific market and among companies with significant SaaS-to-warehouse integration needs.
Open-source data orchestration platform with asset-centric pipeline model; software-defined assets providing automatic lineage and selective materialization over Airflow's task-first approach.
About
Dagster is an open-source data orchestration and pipeline development platform that reimagines how data pipelines are built by modeling data assets (tables, ML models, reports) explicitly rather than just scheduling jobs. Founded in 2018 by Nick Schrock (creator of GraphQL) and headquartered in San Francisco, Dagster Labs raised approximately $75 million and has built a growing community of data engineers who prefer its asset-centric approach over traditional task-centric orchestration tools like Apache Airflow.
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