Edelbyte Raises $45M Series A for One Data Engine Built by Kusto Veterans
A one-year-old Israeli data company is now valued at $500M. Edelbyte raised a $45M Series A led by Quiet Capital, with all existing investors back plus QP Ventures, Startpoint Capital and Cerca Partners. The earlier $25M seed was led by Sequoia with Greenoaks and Swish Ventures, so the total is $70M. Everything here comes from Calcalist's report; no company release was found: https://www.calcalistech.com/ctechnews/article/rk9dvkfrmx
The founding team is the story. Avner Aharoni (CEO), Evgeney Ryzhyk (CTO), Alexander Sloutsky and Yoni Leibowitz all come from Microsoft, and Ryzhyk and Sloutsky were on the original Kusto team, the engine behind Azure Data Explorer. Founded in November 2025, about 40 people across Tel Aviv and San Francisco, and the company says it already runs petabyte-scale systems for Fortune 500 customers.
The pitch is one engine for analytics, text search, geospatial queries and AI workloads, so data doesn't get copied into four different systems. It positions itself against Snowflake, Databricks and ClickHouse and puts the market at $300B. The money goes to hiring and taking the product to more large customers.
Why it matters for agents: an agent asking questions of company data runs a mix of SQL, keyword search and vector lookup in a single turn. Today that usually means three stores and a pile of sync jobs. A team that already built one of Microsoft's fastest log engines betting that the agent era needs one engine, not three, is a bet worth watching, even if "kill Snowflake" pitches have a long graveyard.
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The founding team is the story. Avner Aharoni (CEO), Evgeney Ryzhyk (CTO), Alexander Sloutsky and Yoni Leibowitz all come from Microsoft, and Ryzhyk and Sloutsky were on the original Kusto team, the engine behind Azure Data Explorer. Founded in November 2025, about 40 people across Tel Aviv and San Francisco, and the company says it already runs petabyte-scale systems for Fortune 500 customers.
The pitch is one engine for analytics, text search, geospatial queries and AI workloads, so data doesn't get copied into four different systems. It positions itself against Snowflake, Databricks and ClickHouse and puts the market at $300B. The money goes to hiring and taking the product to more large customers.
Why it matters for agents: an agent asking questions of company data runs a mix of SQL, keyword search and vector lookup in a single turn. Today that usually means three stores and a pile of sync jobs. A team that already built one of Microsoft's fastest log engines betting that the agent era needs one engine, not three, is a bet worth watching, even if "kill Snowflake" pitches have a long graveyard.
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