NeoApps or Continual? A Comprehensive Review

No-code app builder

User-centric design

User stories integration

Clear requirements definition

User journeys creation

Adaptable database structure

Mapping API workflows

Third-party process integration

Automated code generation

REST API adaptability

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

Limited sector-specific modules

Predetermined database structure

Lacks advanced customization

Redeployment may be complicated

No offline functionality

No Desktop Applications

Limited third-party integrations

No multilingual support

Dependency on REST API

Closed-source tool

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