Rivery vs Hex Technologies
Side-by-side comparison of AI visibility scores, market position, and capabilities
Tel Aviv and NYC data pipeline platform raised $50M+ from Salesforce Ventures; unified ELT, reverse ETL, and workflow orchestration for cloud data warehouses with 200+ source integrations.
About
Rivery is a data pipeline and orchestration platform founded in 2018 and headquartered in Tel Aviv, Israel, with offices in New York City. The company was founded by Itamar Ben Hemo and Or Lenchner to build a unified data operations platform that covers data ingestion, transformation, reverse ETL (data activation), and workflow orchestration in a single environment. Rather than requiring data teams to stitch together separate tools for each stage of the data lifecycle, Rivery provides an integrated platform where all data workflows — from source connection to downstream activation — are managed and monitored in one place.\n\nRivery raised $50 million in funding from investors including Salesforce Ventures, YL Ventures, and Entrée Capital. The platform supports ingestion from more than 200 sources, in-pipeline transformations, and native reverse ETL to sync data from warehouses back into operational tools like Salesforce, HubSpot, and customer data platforms. Its orchestration engine allows teams to build dependency graphs across pipelines, trigger workflows based on events or schedules, and monitor data flow health through a unified dashboard. Rivery's integrated approach reduces the operational overhead of managing multiple single-function tools that each require separate infrastructure, monitoring, and maintenance.\n\nRivery serves data teams at mid-market and enterprise companies across e-commerce, fintech, and media who need a flexible, cloud-native data operations platform without the deployment complexity of open-source tools. The platform runs fully managed in the cloud with Rivery handling all infrastructure, scaling, and maintenance. Its visual pipeline builder makes it accessible to data analysts and business intelligence developers without deep engineering backgrounds.
San Francisco CA collaborative data workspace; raised $52M+; combines SQL, Python, and AI in a notebook-style environment for data teams and stakeholders.
About
Hex Technologies is a data workspace and collaborative analytics platform founded in 2021 and headquartered in San Francisco, California. The company was founded by Barry McCardel and Caitlin Colgrove to build a modern analytics environment that feels natural to data scientists and analysts but produces outputs that business stakeholders can actually consume. Traditional Python notebooks like Jupyter are powerful for analysis but produce outputs that non-technical users cannot easily explore or interact with. Hex bridges this gap by enabling analysts to write SQL and Python in a notebook-style interface and publish the results as interactive data apps.\n\nHex raised $52 million in funding from investors including Andreessen Horowitz, Redpoint Ventures, and Bain Capital Ventures. Its platform provides a shared, cloud-hosted notebook environment where data teams collaborate on analyses in real time — multiple analysts can work in the same project simultaneously, similar to Google Docs for data work. Projects can be published as interactive data apps with filters, dropdowns, and visualizations that business users can explore without needing to understand the underlying code. This analytics-to-app publishing workflow makes Hex a practical replacement for both ad hoc analysis in notebooks and static dashboard tools.\n\nHex's AI capabilities include Magic, an AI coding assistant that helps analysts write SQL and Python, explain unfamiliar code, generate transformations from natural language descriptions, and debug errors. The platform connects to Snowflake, BigQuery, Redshift, Databricks, DuckDB, and major databases. Its versioning and scheduling capabilities bring production-grade reliability to analysis projects, and its workspace collaboration features make it well-suited for analytics engineering teams at data-driven companies.
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