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Continual vs Graft

Continual or Graft? A Comprehensive Review

Continual

Continual

Cloud-based predictive modeling using SQL.

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Graft

Graft

Data app dev for scalable solutions.

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Overview

Description

Continual is the go-to operational AI platform for predictive modeling in the cloud. It simplifies the process of building and maintaining models by using SQL and dbt declarations,

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Graft is a powerful data app development tool that enables the creation and scaling of AI solutions for businesses. Rather than requiring expert knowledge in machine learning, Graft

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Pricing Options

  • No free trial
  • Not Available
  • No free trial
  • $20, month
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Features

Total Features

Features
Features

Unique Features

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Pricing

Pricing Option

      Starting From

      • Not Available
      • $20, month
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      Other Details

      Customer Types

      • No customer type information available
      • No customer type information available
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      User Reviews

      User Ratings

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      Pros

      • Cloud-based predictive modeling

      • Uses SQL for app creation

      • Works with BigQuery

      • Snowflake

      • Redshift

      • and Databricks

      • No need for complex infrastructure

      • Models improve continually

      • Data and models stored on warehouse

      • Easily accessible to operational and BI tools

      not-available-review

      Cons

      • SQL-centric

      • Limited to cloud data platforms

      • Dependency on modern data stacks

      • No MLOPS infrastructure

      • Limited extensibility (Python only)

      • Dependent on dbt compatibility

      • Not suitable for traditional data management systems

      • Data must be on the same warehouse

      • No mention of multilingual support

      • Dependent on continuous access to data warehouse

      not-available-review

      Media and Screenshots

      Screenshots

      Continual
      Graft

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      Disclaimer: This research has been collated from a variety of authoritative sources. We welcome your feedback at [email protected].

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