Varada provides a data virtualization platform that layers an indexing system atop data lakes and uses machine learning to pre-cache workloads, accelerating query performance. The platform leverages the open-source Presto SQL engine as one of its cornerstones. Its indexing approach reduces the need to replicate data, lowering storage and compute costs while allowing data to remain in customers' virtual private clouds. Varada is not offered as a SaaS product, which MizMaa noted preserves buyers' cloud-provider discounts. The system also includes resource-allocation controls so different users or groups can be given different bandwidth. The company positions itself toward technologists inside enterprises and contrasts its lake-centric approach with solutions that move or copy customer data. Varada provides an on-demand SQL analytics platform that lets data practitioners define any dataset of interest directly on the data lake and analyze it interactively using SQL or BI tools without data preparation or modeling. Its inline indexing technology enables interactive sub-second analytics across any dimension or schema on petabyte-scale data lakes. The company targets large-scale analytics workloads by operating directly on data lakes rather than requiring ETL or separate warehouses. Varada intends to use the new funding to expand business operations and accelerate development efforts. The company was co-founded by Tal Ben Moshe, Roman Vainbrand and David Krakov and is based in Tel Aviv.

Total raised

$20M

Funding rounds

2

Latest round

Series A

Latest activity

Sep 2020