The data infrastructure
you need, effortlessly

The data infrastructure
you need, effortlessly

The data infrastructure
you need, effortlessly

The easiest way to build cloud data infrastructure for smaller, less-technical teams.
Build batch & real-time data pipelines, get rapid data insights, all through a user-friendly dashboard.

Get Started

The easiest way to build cloud data infrastructure for smaller, less-technical teams.
Build batch & real-time data pipelines, get rapid data insights, all through a user-friendly dashboard.

Get Started

The easiest way to build cloud data infrastructure for smaller, less-technical teams.
Build batch & real-time data pipelines, get rapid data insights, all through a user-friendly dashboard.

Get Started

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Raw data to actionable insights, in a few clicks

Raw data to actionable insights, in a few clicks

Raw data to actionable insights, in a few clicks

Add breakpoints to your blank page, then drop sections to have them responsive out of the box.

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Raw data to actionable insights, in a few clicks

Unlock your data with a few clicks instead of code.

Replace verbose code with reusable blocks

Replace verbose code with reusable blocks

Replace verbose code with reusable blocks

10x your pipeline development time with easy, reusable blocks

Pipeline Cloning

Easily clone existing pipelines to avoid repetitive setup

Replace long-winded code with editable blocks

Replace long-winded code with editable blocks

Traditional data is locked away from business users. Access that data with a few clicks instead of code.

Traditional data is locked away from business users. Access that data with a few clicks instead of code.

class GetDistanceTransformer(Transformer):

    def __init__(self, start_column, end_column, output_column):
        self.start_column = start_column
        self.end_column = end_column
        self.output_column = output_column

    def transform(self, df):   
        def calculate_distance_km(user_coords, facility_coords):
            user_lat, user_lon = map(float, user_coords.split(","))
            facility_lat, facility_lon = map(float, facility_coords.split(","))
            return geodesic((user_lat, user_lon), (facility_lat, facility_lon)).kilometers

        calculate_distance_km_udf = F.udf(calculate_distance_km, FloatType())                   
        def calculate_distance_mi(user_coords, facility_coords):
            user_lat, user_lon = map(float, user_coords.split(","))
            facility_lat, facility_lon = map(float, facility_coords.split(","))
            return geodesic((user_lat, user_lon), (facility_lat, facility_lon)).miles

        calculate_distance_mi_udf = F.udf(calculate_distance_mi, FloatType())
        df_with_distances = df.withColumn(
            self.output_column,
            calculate_distance_mi_udf(df[self.start_column], df[self.end_column]),
        )

        return df_with_distances

Raw data to actionable insights, in a few clicks

Raw data to actionable insights, in a few clicks

Traditional data is locked away from business users. Access that data with a few clicks instead of code.

Traditional data is locked away from business users. Access that data with a few clicks instead of code.

Open-Source

Free

Low-code data transformation,

connector blocks

Databricks deployment

Job scheduling

Github

Cloud

$200

p/month/seat

Everything in Open-Source

Cloud dashboard to build data

pipelines

Scheduling through UI

Full lifecycle - develop, test, CI/CD

Enterprise

Custom

Everything in Cloud

Unlimited developer seats

Block-level GPT copilot

24/7 Enterprise Support

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