DevOps continues to receive a lot of attention as a wave of companies develop more sophisticated tools to help developers manage increasingly complex architectures and workloads. In the latest development, Data band – an AI-powered observability platform for data pipelines, specifically to detect when something is wrong with a data source when an engineer uses a disparate set of data management tools – a closed a round of $ 14.5 million.
Josh Benamram, the CEO who co-founded the company with Victor Shafran and Evgeny Shulman, said Databand’s plans called for more hires; continue to add customers for your existing product; expand the library of tools it provides to users to cover a growing landscape of DevOps software, where it is a big supporter of open source resources
; as well as investing in the next steps of your own trading product. This will include more solutions once the issues are identified – that is, in addition to identifying issues, engineers can also start to fix them automatically.
Series A is led by Accel with participation from Blumberg Capital, Lerer Hippeau, Ubiquity Ventures, Differential Ventures and Bessemer Venture Partners. Blumberg led the company’s 2018 funding round. He has now raised around $ 18.5 million and is not disclosing the valuation.
The problem Databand is solving is one that is becoming more urgent and troublesome day by day (because it exponential annual increase in zettabytes of data worldwide). And as data workloads continue to increase in size and use, they become increasingly complex.
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On top of that, today there is a wide range of applications and platforms that a typical organization will use to manage source hardware, storage, usage, etc. This means that when there are flaws in a data source, it can be difficult to pinpoint where and what the problem may be. Doing it manually can be time consuming or even impossible.
“Our users were in a constant battle with the ETL (mining freight processing) logic,” said Benamram, who told me about New York (the company is based there and in Tel Aviv, and also developers and operations in Kiev.). “Users did not know how to organize their tools and systems to produce reliable data products.”
It’s really hard to focus on the flaws, he said, when engineers balance instrument panels, model machine performance, and other time demands; And that’s before considering when and if a data provider may have changed an API at any given time, which could also throw the data source off balance completely.
And if you’ve ever received this data, you know how frustrating (and possibly worse, disastrous) bad data can be. Benamram said it’s not uncommon for engineers to forget anomalies completely and only get caught by “CEOs looking at their dashboards and suddenly they think something is wrong.” It is not a big step.
Databand’s approach is to use Big Data to better manage Big Data: it processes a variety of information, including pipeline metadata such as logs, runtime information, and data profiles, as well as customer information. ‘Airflow, Spark, Snowflake and other sources. , and puts the resulting data on a single platform, to give engineers a single view of what’s going on, better see where the bottlenecks or anomalies are and why.
There are a number of other companies that are creating data observability tools; Splunk is perhaps one of the most obvious, but also one of the smallest, like helmet Yes Rivery. These companies could go further in the area that Databand has identified and is correcting, but for now, Databand’s specific focus on identifying and helping engineers correct anomalies has given it a profile. and a strong position.
Accel partner Seth Pierrepont said maybe Databand caught the VC’s attention in the best possible way: Accel needed a solution like this for its own internal work.
“The observability of the data pipeline is a challenge our internal data team at Accel was struggling with. Even at our relatively small scale, we had issues with the reliability of our weekly data outputs, and our team found Databand as a solution, ”he says. “As businesses across industries look to become more data-driven, Databand offers an essential product that ensures reliable delivery of high-quality data for businesses. Josh, Victor and Evgeny have extensive experience in this area and we have been impressed with their thoughtful and open approach to helping data engineers better manage their data channels with Databand.
The company is also used by data teams at large Fortune 500 companies and small startups.