Comparing dlt (Data Load Tool) with Informatica PowerCenter and Weld
Carolina Russ6 min read
What is dlt (Data Load Tool)
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.
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)
High volume, low latency, hard-to-build stuff is complicated. It really depends.
What is Informatica PowerCenter
Informatica PowerCenter is a legacy enterprise-grade ETL platform that provides a visual designer, metadata management, scheduling, and monitoring for complex, large-scale ETL workloads. It supports a vast range of sources (mainframes, relational, NoSQL, cloud) and advanced transformations (data quality, profiling, master data management) within the Informatica ecosystem.
Pros
- Extremely powerful and scalable for enterprise ETL with parallel processing and pushdown optimization.
- Comprehensive transformation library, data quality, and metadata management integrated in the platform.
- Robust scheduling and workflow orchestration with detailed logging and recovery capabilities.
- Supports heterogeneous environments: on-prem, cloud, hybrid, and mainframe data sources.
Cons
- High total cost of ownership: expensive licensing, dedicated infrastructure, and specialized admins.
- User interface is dated; development and maintenance require specialized training, increasing time to onboard new users.
- Less agility for rapidly changing data needs vs. modern cloud-native ETL tools; upgrades and patches are time-consuming processes.
G2 Reviews:
What I like about Informatica PowerCenter
Informatica powercenter has been a classic , it has been in the industry for around 30 years and still is very relavant to the point , provide every possible connector and provides best mapping tools.
What I dislike about Informatica PowerCenter
the UI looks very old and sometimes it is very difficult to handle big big mappings as it needs lot of experience
What is Weld
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.
Pros
- 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
Cons
- 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:
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.
Informatica PowerCenter
PowerCenter’s Designer and Workflow Manager GUIs are comprehensive but dated. Developers need formal training to use transformation and mapping components effectively. The metadata integration assists with governance but adds complexity.
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.
Informatica PowerCenter
Pricing is custom enterprise quotes—often $100k+ per year depending on nodes and users. Best for large enterprises that need high SLAs and rich feature sets; impractical for startups or small teams.
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.
Informatica PowerCenter
Includes: visual mapping designer, advanced transformations (data cleansing, lookups, aggregation), parallel processing, workflow orchestration, metadata manager, data quality, master data management, and extensive connectivity (mainframe to cloud).
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.
Informatica PowerCenter
Highly customizable via Expression Transformations, Java Transformations, and stored procedure calls. Integration with command tasks allows custom scripts. However, it’s not open-source; you rely on Informatica for feature updates.
Summary of dlt (Data Load Tool) vs Informatica PowerCenter vs Weld
| Weld | dlt (Data Load Tool) | Informatica PowerCenter | |
|---|---|---|---|
| Connectors | 200+ | 60+ | 200+ |
| Price | $79 / 5M Active Rows | Free (open-source) | Enterprise licensing (six-figure annual contracts) |
| Free tier | No | No | No |
| Location | EU | DE | Redwood City, CA, USA (Informatica HQ) |
| Extract data (ETL) | Yes | Yes | Yes |
| Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | Yes | No |
| Transformations | Yes | Yes | Yes |
| AI Assistant | Yes | No | No |
| On-Premise | No | Yes | Yes |
| 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 | No |
| Two-Way Sync | Yes | No | No |
| dbt Core Integration | Yes | No | No |
| 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), Informatica PowerCenter, 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..
- Informatica PowerCenter: includes: visual mapping designer, advanced transformations (data cleansing, lookups, aggregation), parallel processing, workflow orchestration, metadata manager, data quality, master data management, and extensive connectivity (mainframe to cloud). . pricing is custom enterprise quotes—often $100k+ per year depending on nodes and users. best for large enterprises that need high slas and rich feature sets; impractical for startups or small teams. .
- 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 $79 for 5 million active rows, making it more affordable and predictable, especially for small to medium-sized enterprises..
