Comparing dlt (Data Load Tool) with Hevo and Weld



What is dlt (Data Load Tool)
Pros
- 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.)
Cons
- 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:
What I like about dlt (Data Load Tool)
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.
What I dislike about dlt (Data Load Tool)
What is Hevo
Pros
- Supports both ELT, ELT, and reserve ELT
- Plenty of fully maintained connectors
- Great for non-technical users
- Simple UI that's easy to work with
- Affordable pricing
Cons
- Limited features for more advanced use cases
- Limited custom scheduling features
- Only 50 connectors are available on the Free plan
- Lack of flexibility when wanting to edit pipelines
- Error messages and status codes could be better
As one reviewer on G2 puts it: :
What I like about Hevo
Hevo is really good for normal pipelines, but it has some limitations for more complex use cases.
What I dislike about Hevo
What is Weld
Pros
- Premium quality connectors and reliability
- User-friendly and easy to set up
- AI assistant
- Very competitive and easy-to-understand pricing model
- Reverse ETL option
- Lineage, orchestration, and workflow features
- Advanced transformation and SQL modeling capabilities
- Ability to handle large datasets and near real-time data sync
- Combines data from a wide range of sources for a single source of truth
Cons
- Requires some technical knowledge around data warehousing and SQL
- Limited features for advanced data teams
A reviewer on G2 said:
What I like about Weld
First and foremost, Weld is incredibly user-friendly. The graphical interface is intuitive, which makes it easy to build data workflows quickly and efficiently. Even with little experience in SQL and pipeline management, we found that Weld was straightforward and easy to use. What really impressed me, however, was Weld's flexibility. It was able to handle data from a wide variety of sources, including SQL databases, Google Sheets, and even APIs. The solution also allowed us to customize my data transformations in a way that best suited my needs. Whether I needed to clean data, join tables, or aggregate data, Weld had the necessary tools to accomplish the task. Weld's performance was also exceptional. I was able to run large-scale ETL jobs quickly and efficiently, with minimal downtime via a Snowflake instance and visualization via own-hosted Metabase. The solution's scalability meant that I could process more data without any issues. Another standout feature of Weld was its support. I never felt lost or unsure about how to use a particular feature, as the support team was always quick to respond to any questions or concerns that I had. Overall, I highly recommend Weld as an ETL solution. Its user-friendliness, flexibility, performance, and support make it an excellent choice for anyone looking to streamline their data integration processes. I will definitely be using Weld for all my ETL needs going forward.
What I dislike about Weld
Weld is still limited to a certain number of integrations - although the team is super interested to hear if you need custom integrations.
Feature-by-Feature Comparison
Ease of Use & Interface
dlt (Data Load Tool)
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.
Hevo
Hevo is designed with non-technical users in mind, offering a simple UI and code-free capabilities, making it easy for beginners to use.
Pricing & Affordability
dlt (Data Load Tool)
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.
Hevo
Hevo offers affordable pricing and a free plan with limited connectors, making it accessible for startups and small businesses. However, the costs can rise with data volume and feature needs.
Feature Set
dlt (Data Load Tool)
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.
Hevo
Hevo supports ETL, ELT, and reverse-ETL, making it versatile for different data needs. It also has plenty of fully maintained connectors, although it may lack some advanced features required by seasoned data professionals.
Flexibility & Customization
dlt (Data Load Tool)
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.
Hevo
While Hevo is great for non-technical users, it lacks flexibility and customization options for more complex data tasks, making it less suitable for advanced data teams.
Summary of dlt (Data Load Tool) vs Hevo vs Weld
Weld | dlt (Data Load Tool) | Hevo | |
---|---|---|---|
Connectors | 200+ | 60+ | 150+ |
Price | $79 / No data volume limits | Free (open-source) | $299 / 5M rows |
Free tier | No | No | Yes |
Location | EU | DE | INDIA |
Extract data (ETL) | Yes | Yes | Yes |
Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | Yes | Yes |
Transformations | Yes | Yes | Yes |
AI Assistant | Yes | No | No |
On-Premise | No | Yes | No |
Orchestration | Yes | No | No |
Lineage | Yes | No | No |
Version control | Yes | Yes | No |
Load data to and from Excel | Yes | No | No |
Load data to and from Google Sheets | Yes | No | No |
Two-Way Sync | Yes | No | No |
dbt Core Integration | Yes | No | Yes |
dbt Cloud Integration | Yes | No | No |
OpenAPI / Developer API | Yes | Yes | Yes |
G2 Rating | 4.8 | 4.3 |
Conclusion
You’re comparing dlt (Data Load Tool), Hevo, Weld. Each of these tools has its own strengths:
- dlt (Data Load Tool): 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.. 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..
- Hevo: hevo supports etl, elt, and reverse-etl, making it versatile for different data needs. it also has plenty of fully maintained connectors, although it may lack some advanced features required by seasoned data professionals.. hevo offers affordable pricing and a free plan with limited connectors, making it accessible for startups and small businesses. however, the costs can rise with data volume and feature needs..
- Weld: 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.. weld offers a straightforward and competitive pricing model, starting at $99 for 2 million active rows, making it more affordable and predictable, especially for small to medium-sized enterprises..