Rivery vs Databricks
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.
$4.8B revenue run-rate; 55% YoY growth; $134B valuation (Series L). Mosaic AI for enterprise LLM fine-tuning and inference; Unity Catalog for data governance. DBRX open-source model; every major enterprise AI deployment runs on the lakehouse.
About
Databricks was founded in 2013 by the original creators of Apache Spark — Ali Ghodsi, Matei Zaharia, and five other UC Berkeley researchers — to unify data engineering, analytics, and machine learning on a single platform. The company commercialized the lakehouse architecture, combining the flexibility of data lakes with the reliability of data warehouses. Databricks runs on AWS, Azure, and GCP and leads the commercial distribution of the open-source Delta Lake and MLflow projects.\n\nThe platform includes the Databricks Lakehouse for unified data processing, Unity Catalog for governance and lineage tracking, and Mosaic AI for enterprise LLM fine-tuning, model serving, and generative AI application development. It supports data engineering, SQL analytics, BI, feature engineering, and model training within a single governance perimeter, serving enterprises in financial services, healthcare, manufacturing, and media.\n\nDatabricks achieved a $4.8 billion annualized revenue run-rate in early 2025 with 55% year-over-year growth and a $62 billion valuation from its Series L round — one of the most valuable private software companies globally. Its dual role as the leading commercial lakehouse vendor and steward of influential open-source projects gives it a unique ecosystem advantage as enterprises accelerate investment in AI infrastructure.
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