What I like about Dataddo
“It is so user friendly and doesnt have any learning curve. Any user can really understand and create their own custom flows without any external support”
You’re comparing Dataddo vs dlt (Data Load Tool) vs Weld. Explore how they differ on connectors, pricing, and features.


Loved by data teams from around the world
| Weld | Dataddo | dlt (Data Load Tool) | |
|---|---|---|---|
| Connectors | 200+ | 398+ | 60+ |
| Price | $99 / 5M Active Rows | $99.00 / mo for 3 data flows to sync data between any source and destination | Free (open-source) |
| Free tier | |||
| Location | EU | US/EU | DE |
| Extract data (ETL) | |||
| Sync to HubSpot, Salesforce, Klaviyo, Excel (reverse ETL) | |||
| Transformations | |||
| AI Assistant | |||
| On-Premise | |||
| Orchestration | |||
| Lineage | |||
| Version control | |||
| Load to/from Excel | |||
| Load to/from Google Sheets | |||
| Two-Way Sync | |||
| dbt Core Integration | |||
| dbt Cloud Integration | |||
| OpenAPI / Developer API | |||
| G2 rating | 4.8 | 4.7 | — |
Overview
Dataddo is a fully managed, no-code data integration platform designed for business users, marketers, and analysts who need quick access to data without engineering support. It supports over 300 prebuilt connectors to cloud apps, databases, and BI tools, and offers flexible data flows for ETL, ELT, reverse ETL, and dashboard integrations. If a specific connector isn’t available, Dataddo will build it on request. The platform emphasizes ease of use, with automated handling of API changes, built-in pipeline monitoring, and a “SmartCache” feature that temporarily stores historical data, allowing teams to run reports without immediately setting up a data warehouse. With support for secure data practices (SOC 2, ISO 27001, GDPR compliance) and simple, transparent pricing plans, including a free tier, Dataddo is ideal for organizations looking to centralize data quickly and with minimal overhead.

No-code interface makes setup simple for non-technical users.
Integrates with 300+ platforms, including many marketing and CRM tools.
Onboarding and connector requests are generally well-handled.
Offers competitive pricing, especially for small teams.
Some users report delays for complex issues.
New or niche sources may not be instantly available.
Cancelling or modifying plans can be frustrating.
G2 Review:
“It is so user friendly and doesnt have any learning curve. Any user can really understand and create their own custom flows without any external support”
“If a flow is created, Dataddo needs to introduce how to add more features in the flow (maybe edit columns or add/remove them instead of creating and replacing with a net new flow).”
Overview
Dlt (data load tool) is an open-source Python library for building modern data pipelines with a code-first approach. It lets developers define ETL or ELT workflows directly in Python, making it highly flexible and easy to embed into orchestration tools like Airflow, Dagster, or Prefect. dlt comes with pre-built connectors for popular data sources, and handles schema inference, incremental loading, normalization, and retry logic automatically. It supports destinations like BigQuery, Snowflake, Redshift, and DuckDB, and is designed to reduce boilerplate while giving teams full control over their data workflows.

Open-source and free to use
High flexibility and control via Python code
60+ pre-built connectors with automatic schema evolution
Built-in incremental loading and state management
Embeddable in any orchestration (Airflow, Prefect, cron, etc.)
No graphical UI—code-first, so not accessible to non-developers
Requires engineering effort to deploy and schedule (no managed SaaS)
Limited built-in transformations compared to dedicated ETL tools
Monitoring and observability must be built around code (no native dashboard)
Smaller community and support compared to more established tools
A reviewer on Medium:
“dlt is lightweight, customizable, and removes a lot of the boilerplate around API ingestion. With just a few lines of Python, we were able to create robust pipelines that handle schema changes and incremental loads seamlessly.”
“High volume, low latency, hard-to-build stuff is complicated. It really depends.”
Overview
Weld is a powerful ETL platform that seamlessly integrates ELT, data transformations, reverse ETL, and AI-assisted features into one user-friendly solution. With its intuitive interface, Weld makes it easy for anyone, regardless of technical expertise, to build and manage data workflows. Known for its premium quality connectors, all built in-house, Weld ensures the highest quality and reliability for its users. It is designed to handle large datasets with near real-time data synchronization, making it ideal for modern data teams that require robust and efficient data integration solutions. Weld also leverages AI to automate repetitive tasks, optimize workflows, and enhance data transformation capabilities, ensuring maximum efficiency and productivity. Users can combine data from a wide variety of sources, including marketing platforms, CRMs, e-commerce platforms like Shopify, APIs, databases, Excel, Google Sheets, and more, providing a single source of truth for all their data.
Lineage, orchestration, and workflow features
Ability to handle large datasets and near real-time data sync
ETL + reverse ETL in one
User-friendly and easy to set up
Flat monthly pricing model
200+ connectors (Shopify, HubSpot, etc.)
AI assistant
Requires some technical knowledge around data warehousing and SQL
Limited features for advanced data teams
Focused on cloud data warehouses
A reviewer on G2 said:
“Weld is still limited to a certain number of integrations - although the team is super interested to hear if you need custom integrations.”




Side-by-side

Dataddo offers a clean, intuitive no-code interface that allows users to set up data flows quickly. The drag-and-drop flow builder and prebuilt connectors minimize the learning curve, making it accessible for non-technical users.

dlt has no graphical interface—pipelines are defined in Python code, making it easy for developers comfortable with code but inaccessible to non-technical users.
Weld is highly praised for its user-friendly interface and intuitive design, which allows even users with minimal SQL experience to manage data workflows efficiently. This makes it an excellent choice for smaller data teams or businesses without extensive technical resources.
Side-by-side
Dataddo offers a clean, intuitive no-code interface that allows users to set up data flows quickly. The drag-and-drop flow builder and prebuilt connectors minimize the learning curve, making it accessible for non-technical users.
dlt has no graphical interface—pipelines are defined in Python code, making it easy for developers comfortable with code but inaccessible to non-technical users.
Weld is highly praised for its user-friendly interface and intuitive design, which allows even users with minimal SQL experience to manage data workflows efficiently. This makes it an excellent choice for smaller data teams or businesses without extensive technical resources.
Side-by-side

Pricing is straightforward and competitive, with plans starting at $99/month for three data flows. The free tier allows users to test the platform with limited functionality before committing to a paid plan.

As an open-source library, dlt is free to use. Users only pay for the infrastructure required to run pipelines, making it highly affordable compared to paid SaaS solutions.
Weld offers a straightforward and competitive pricing model, starting at $79 for 5 million active rows, making it more affordable and predictable, especially for small to medium-sized enterprises.
Side-by-side
Pricing is straightforward and competitive, with plans starting at $99/month for three data flows. The free tier allows users to test the platform with limited functionality before committing to a paid plan.
As an open-source library, dlt is free to use. Users only pay for the infrastructure required to run pipelines, making it highly affordable compared to paid SaaS solutions.
Weld offers a straightforward and competitive pricing model, starting at $79 for 5 million active rows, making it more affordable and predictable, especially for small to medium-sized enterprises.
Side-by-side

Dataddo supports over 300 connectors, ETL/ELT workflows, reverse ETL capabilities, data transformations, and built-in monitoring.

dlt provides core pipeline features: connector library, schema inference, incremental loading, and state management. It supports major destinations (Snowflake, BigQuery, Redshift, PostgreSQL, Databricks) and allows in-Python transformations or dbt integration.
Weld integrates ELT, data transformations, and reverse ETL all within one platform. It also provides advanced features such as data lineage, orchestration, workflow management, and an AI assistant, which helps in automating repetitive tasks and optimizing workflows.
Side-by-side
Dataddo supports over 300 connectors, ETL/ELT workflows, reverse ETL capabilities, data transformations, and built-in monitoring.
dlt provides core pipeline features: connector library, schema inference, incremental loading, and state management. It supports major destinations (Snowflake, BigQuery, Redshift, PostgreSQL, Databricks) and allows in-Python transformations or dbt integration.
Weld integrates ELT, data transformations, and reverse ETL all within one platform. It also provides advanced features such as data lineage, orchestration, workflow management, and an AI assistant, which helps in automating repetitive tasks and optimizing workflows.
Side-by-side

While Dataddo is primarily designed for ease of use, it still offers flexibility through its wide range of connectors and the ability to create custom data flows. However, it may not provide the same level of customization as more technical platforms.

Because pipelines are written in Python, dlt offers unmatched customization—developers can fetch from any API, implement custom logic, and integrate with any orchestration or monitoring framework. This flexibility requires engineering investment but allows tailor-made solutions.
Weld offers advanced SQL modeling and transformations directly within its platform with the help of AI, providing users with unparalleled control and flexibility over their data. Leveraging its powerful AI capabilities, Weld automates repetitive tasks and optimizes data workflows, allowing teams to focus on getting value and insights. Additionally, Weld's custom connector framework enables users to build connectors to any API, making it easy to integrate new data sources and tailor data pipelines to meet specific business needs. This flexibility is particularly beneficial for teams looking to customize their data integration processes extensively and maximize the utility of their data without needing external tools.
Side-by-side
While Dataddo is primarily designed for ease of use, it still offers flexibility through its wide range of connectors and the ability to create custom data flows. However, it may not provide the same level of customization as more technical platforms.
Because pipelines are written in Python, dlt offers unmatched customization—developers can fetch from any API, implement custom logic, and integrate with any orchestration or monitoring framework. This flexibility requires engineering investment but allows tailor-made solutions.
Weld offers advanced SQL modeling and transformations directly within its platform with the help of AI, providing users with unparalleled control and flexibility over their data. Leveraging its powerful AI capabilities, Weld automates repetitive tasks and optimizes data workflows, allowing teams to focus on getting value and insights. Additionally, Weld's custom connector framework enables users to build connectors to any API, making it easy to integrate new data sources and tailor data pipelines to meet specific business needs. This flexibility is particularly beneficial for teams looking to customize their data integration processes extensively and maximize the utility of their data without needing external tools.
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