Arroyo

Arroyo

Arroyo is the easiest way to run SQL queries against your real-time data in Kafka.

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DateInvestorsAmountRound
-investor

€0.0

round
N/A

€0.0

round
*

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Acquisition
Total Funding000k

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Revenues, earnings & profits over time
USD2023
Revenues0000
EBITDA0000
Profit0000
EV0000
EV / revenue00.0x
EV / EBITDA00.0x
R&D budget0000

Source: Dealroom estimates

More about Arroyo
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Arroyo.dev is a cutting-edge startup specializing in serverless stream processing, which means they help businesses handle and analyze data in real-time without the need for managing servers or clusters. This makes it easier and more cost-effective for companies to process large volumes of data quickly. Arroyo.dev primarily serves businesses that rely on real-time data analytics, such as those in finance, e-commerce, and tech industries.

The company operates in the data infrastructure market, focusing on stream processing. Stream processing is a method of continuously analyzing data as it is produced, which is crucial for applications that need immediate insights, like fraud detection, real-time analytics, and machine learning.

Arroyo.dev's business model is based on a fully serverless architecture. This means clients do not have to worry about the underlying hardware or software infrastructure. Instead, they can connect their existing data streams from platforms like Kafka or Kinesis, and use SQL (a standard language for managing and manipulating databases) to build and manage their data pipelines. This approach allows clients to transform, filter, aggregate, and join data streams with sub-second results, making it highly efficient.

The company makes money by offering its platform as a service. Clients pay for the usage of Arroyo.dev's stream processing capabilities, which can automatically scale from handling a few events to millions per second. This scalability ensures that businesses only pay for what they use, making it a cost-effective solution.

In summary, Arroyo.dev simplifies real-time data processing for businesses, enabling them to gain immediate insights and respond proactively to changing conditions without the complexity and cost of managing their own infrastructure.

Keywords: serverless, stream processing, real-time analytics, data infrastructure, Kafka, Kinesis, SQL, machine learning, fraud detection, scalability.

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