
Ryft
Automated data management platform optimizing Iceberg tables.
Date | Investors | Amount | Round |
---|---|---|---|
* | $8.0m | Seed | |
Total Funding | 000k |
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Ryft is a data management software developer that offers a platform to optimize Apache Iceberg table environments. Founded in 2024 by CEO Yossi Reitblat, CTO Yuval Yogev, and VP of R&D Guy Gadon, the company emerged from stealth in July 2025 with $8 million in seed funding. The round was led by Index Ventures and Bessemer Venture Partners, with participation from executives at firms like Wiz, Zscaler, Crowdstrike, Confluent, and Cisco.
The founding team, friends since high school, previously developed large-scale data systems as software engineers in an elite Israeli military intelligence unit. This experience provided them with insights into the critical need for data flexibility and ownership, which became the foundation for Ryft. The company aims to address the challenges of vendor lock-in, soaring costs, and rigid infrastructure associated with major cloud data platforms like Snowflake, Databricks, and Google.
Ryft's core product is a fully managed, cloud-native data platform built on the open-source Apache Iceberg standard. It automates complex data management tasks such as table maintenance, optimization, compaction, compliance, governance, and disaster recovery. This allows enterprise data engineering teams to retain full ownership and control of their data, decoupling it from any single vendor's ecosystem while providing the flexibility to choose their preferred analytics engines and storage solutions. The platform provides a unified view for monitoring data usage and queries across different engines like Spark and Trino. Revenue is generated through an annual fee based on the volume of data managed. Ryft's client base already includes customers in finance, e-commerce, adtech, gaming, and cybersecurity.
Keywords: data management, Apache Iceberg, data lakehouse, cloud data platform, vendor lock-in, data optimization, data governance, data infrastructure, enterprise data, cloud-native, data engineering, automated table maintenance, open source data, data analytics