Comparing dlt (Data Load Tool) with SnapLogic 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 SnapLogic
Pros
- 500+ Snap connectors covering SaaS, databases, big data, and on-prem sources.
- Visual pipeline designer (Snap Studio) with AI-driven suggestions (Iris) for mapping and transformations.
- Serverless execution with autoscaling and multi-cloud support (AWS, Azure, GCP).
- Supports real-time streaming (buses), batch, and IoT/edge integrations.
Cons
- Premium pricing (connector-based, usage-based) can be cost-prohibitive for SMBs.
- Designer interface can become cluttered when pipelines grow large; performance may degrade.
- Limited offline or self-hosted options; fully SaaS-based.
SnapLogic Documentation:
What I like about SnapLogic
SnapLogic’s Iris AI recommendations help build pipelines faster—very helpful for common transformations and connector configurations.
What I dislike about SnapLogic
Pricing is high; smaller teams may not need such a large connector catalog. The UI can be overwhelming with very large pipelines.
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.
dlt (Data Load Tool) vs SnapLogic: Ease of Use and User 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.
SnapLogic
SnapLogic’s Snap Studio is a React-based canvas where users drag Snaps (pre-built connectors or transforms) into pipelines. Iris AI suggests mappings and transformations, reducing manual work. However, very large pipelines can slow down.
dlt (Data Load Tool) vs SnapLogic: Pricing Transparency and 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.
SnapLogic
SnapLogic’s pricing is typically $50k+ per year for moderate usage; connectors and runtime costs can add up. Large enterprises benefit from the wide connector catalog and AI features, but SMBs may find it expensive relative to needs.
dlt (Data Load Tool) vs SnapLogic: Comprehensive 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.
SnapLogic
Features include: over 500 Snaps, real-time streaming, batch pipelines, AI-driven pipeline recommendations, multi-cloud deployment, built-in data quality, API management, and robust monitoring/alerting.
dlt (Data Load Tool) vs SnapLogic: Flexibility and 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.
SnapLogic
SnapLogic allows custom Snaps to be written in Node.js or Python, enabling bespoke connectors or transforms. Pipelines can be parameterized, embedded into CI/CD, and triggered via REST APIs. However, no self-hosted runtime—is fully SaaS.
Summary of dlt (Data Load Tool) vs SnapLogic vs Weld
Weld | dlt (Data Load Tool) | SnapLogic | |
---|---|---|---|
Connectors | 200+ | 60+ | 500+ |
Price | €99 / 2 connectors | Free (open-source) | Subscription (connector & usage-based; starts ~$50k/year) |
Free tier | No | No | No |
Location | EU | DE | San Mateo, CA, USA |
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 | Yes |
On-Premise | No | Yes | No |
Orchestration | Yes | No | Yes |
Lineage | Yes | No | Yes |
Version control | Yes | Yes | Yes |
Load data to and from Excel | Yes | No | Yes |
Load data to and from Google Sheets | Yes | No | Yes |
Two-Way Sync | Yes | No | Yes |
dbt Core Integration | Yes | No | No |
dbt Cloud Integration | Yes | No | No |
OpenAPI / Developer API | Yes | Yes | Yes |
G2 Rating | 4.8 | 4.4 |
Conclusion
You’re comparing dlt (Data Load Tool), SnapLogic, 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..
- SnapLogic: features include: over 500 snaps, real-time streaming, batch pipelines, ai-driven pipeline recommendations, multi-cloud deployment, built-in data quality, api management, and robust monitoring/alerting. . snaplogic’s pricing is typically $50k+ per year for moderate usage; connectors and runtime costs can add up. large enterprises benefit from the wide connector catalog and ai features, but smbs may find it expensive relative to 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..