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Weld vs Hightouch vs StreamSets Data Collector

You’re comparing Weld vs Hightouch vs StreamSets Data Collector. Explore how they differ on connectors, pricing, and features. Ed Logo

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Weld vs Hightouch vs StreamSets Data Collector

FeatureWeldHightouchStreamSets Data Collector
Core Platform
Price
$79 / 5M Active Rows
Free tier; Growth plans start around $800+/month
Free OSS Data Collector; enterprise DataOps Platform is custom-priced
Free tier
No
Yes
Yes
Location
DK, (EU)
US
San Francisco, CA, USA
Connectors & Sync
Connectors
200+
70+
200+
Extract data (ETL)
Yes
No
Yes
Sync to HubSpot, Salesforce, Klaviyo, Excel (reverse ETL)
Yes
Yes
No
Two-Way Sync
Yes
No
No
Transformations & AI
Transformations
Yes
No
Yes
AI Assistant
Yes
No
No
dbt Core Integration
Yes
Yes
No
dbt Cloud Integration
Yes
No
No
Governance & DevOps
Orchestration
Yes
Yes
Yes
Lineage
Yes
No
Yes
Version control
Yes
Yes
Yes
On-Premise
No
No
Yes
OpenAPI / Developer API
Yes
Yes
No
Integrations
Load to/from Excel
Yes
No
Yes (via file connectors)
Load to/from Google Sheets
Yes
No
No
Ratings
G2 rating
4.8
4.6
4.5

Overview

Weld in Short

Weld is a unified ELT and data activation platform that combines ingestion, modeling, transformations, orchestration, lineage, and reverse ETL in a single SaaS interface. With premium in-house–built connectors, an intuitive UI, and near real-time syncs, Weld enables both technical and non-technical users to create and manage data workflows efficiently. Weld also includes an AI assistant to support SQL modeling, generate transformations, and streamline repetitive tasks. Teams can ingest data from a wide range of sources—including marketing platforms, CRMs, databases, Google Sheets, Excel, and APIs—into their cloud data warehouse and activate it back into business tools.

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Pros

  • Lineage, orchestration, and workflow features included by default

  • Handles large datasets and near real-time data sync

  • ELT and reverse ETL in one platform

  • User-friendly interface with minimal setup required

  • Flat, predictable monthly pricing model

  • 200+ in-house–built, high-quality connectors

  • AI assistant for modeling and transformations

Cons

  • Some SQL knowledge is useful for advanced modeling

  • Optimized for cloud-warehouse workflows (Snowflake, BigQuery, Redshift, etc.)

  • Feature set is streamlined for modern ELT/activation use cases

Reviews & Quotes

A reviewer on G2 said:

What I like about Weld

Weld’s graphical interface is intuitive and easy to work with, even for teams with limited SQL experience. Its flexibility across sources—from databases to Google Sheets and APIs—made onboarding smooth, and performance across larger workloads was consistently strong. Support was responsive and helpful throughout our setup and ongoing use.

Overview

Hightouch in Short

Hightouch is a reverse ETL platform and composable CDP designed to sync data from cloud data warehouses into operational tools such as CRMs, ad platforms, and email providers. It supports SQL-based and no-code audience creation, enabling teams to operationalize warehouse data for sales, marketing, and customer success use cases.

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Pros

  • Audience builder allows non-technical users to create and segment audiences visually

  • Supports 70+ operational destinations across CRM, ads, email, and support

  • Does not store data; reads directly from the warehouse for security

  • Supports near real-time and frequent syncs depending on destination capabilities

  • SQL queries and expressions allow granular control for technical users

  • Strong product documentation, community content, and support resources

Cons

  • Reverse ETL only—requires separate tooling for ingestion or warehouse modeling

  • Usage-based pricing (rows/fields) can increase for high-volume workloads

  • Destination API limits can affect sync frequency and throughput

  • Custom connectors depend on vendor prioritization

  • Complex audience or identity resolution still requires upstream modeling

Reviews & Quotes

Hightouch Product Description:

What I like about Hightouch

Hightouch is the easiest way to sync customer data into tools like CRMs, email platforms, and ad networks, using either SQL or a point-and-click UI without requiring engineering involvement.

Overview

StreamSets Data Collector in Short

StreamSets Data Collector is an open-source data integration engine designed for continuous ingestion, transformation, and delivery. It supports both streaming systems such as Kafka and Kinesis, and batch sources including JDBC and file systems. Pipelines are built using a drag-and-drop canvas, and a key differentiator is Schema Drift Detection, which helps pipelines adapt automatically as input schemas evolve. Commercial editions extend the platform with enterprise monitoring, governance, metadata, and lineage features.

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Pros

  • Schema Drift Detection adjusts dynamically to changes in incoming data schemas.

  • Supports streaming and batch ingestion within the same pipeline.

  • Visual pipeline builder with 200+ processors and connectors.

  • Open-source core available; enterprise offering adds monitoring, lineage, and governance.

Cons

  • Open-source version lacks enterprise monitoring, lineage, and governance.

  • UI performance can degrade with very large or complex pipelines.

  • Advanced pipeline logic often requires Groovy or Java scripting.

Reviews & Quotes

StreamSets Data Operations Platform:

What I like about StreamSets Data Collector

StreamSets’ ability to automatically detect and adapt to schema changes (drift) in streaming sources greatly reduces pipeline failures.

What I dislike about StreamSets Data Collector

The open-source feature set is limited—monitoring, lineage, and enterprise support require the paid DataOps Platform. Debugging complex pipelines can be tricky if not familiar with the UI.

Feature-by-Feature Comparison

Feature
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Ease of Use & Interface

Side-by-side

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Weld’s interface is built for clarity and speed, enabling users with varying levels of technical experience to manage data pipelines and models efficiently. Its built-in lineage and orchestration tools provide transparency across workflows.

hightouch logo

Hightouch provides a modern interface with visual audience building for non-technical teams and SQL-based configuration for advanced users. Mapping and validation workflows are straightforward and approachable.

streamsets logo

StreamSets Data Collector provides a drag-and-drop canvas for assembling origin, processor, and destination stages. Schema drift is surfaced automatically. Simple pipelines are approachable, while advanced transformations may require scripting knowledge.

Pricing & Affordability

Side-by-side

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Weld offers a simple and predictable pricing model starting at $79 for 5 million active rows. This flat, usage-transparent structure makes budgeting straightforward for small and medium-sized teams.

hightouch logo

Hightouch offers a free tier for small workloads. Paid plans scale based on usage, which can be cost-effective for targeted operational syncs but may increase for high-volume enterprise use cases.

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The open-source Data Collector is free. Enterprise capabilities such as monitoring dashboards, lineage, and governance require licensing the DataOps Platform. Pricing varies based on deployments and enterprise features.

Feature Set

Side-by-side

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Weld provides ELT ingestion, SQL-based transformations, reverse ETL activation, data lineage, orchestration, and workflow management in a single platform. Its AI assistant accelerates modeling and transformation tasks.

hightouch logo

Hightouch includes reverse ETL features such as SQL-based syncs, audience building, incremental updates, scheduling, monitoring, alerting, and support for real-time triggers depending on destination APIs. It integrates with dbt and offers API/CLI tools for GitOps workflows.

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Key features include schema drift detection, streaming and batch support, transformation processors, JDBC/Kafka/S3/HDFS connectors, enterprise monitoring and lineage (in paid edition), and containerized deployment.

Flexibility & Customization

Side-by-side

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Users can model data using SQL enhanced by Weld’s AI assistant, automate workflows, and build custom connectors to any API. This provides strong flexibility for teams that want to tailor integrations and transformations within one platform.

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Users can define sync logic via SQL, configure mapping rules, and trigger syncs via API. Hightouch supports webhook destinations and generic connectors, offering additional flexibility while relying on the warehouse for complex transformations.

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Custom processors can be written in Java or Groovy, and pipelines can be parameterized. StreamSets integrates with external orchestrators such as Airflow and monitoring tools like Prometheus or Grafana.

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CUSTOMER STORIES

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Jacob Poulsen, Head of Marketing Expansion at Flatpay logo

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We’re still a team of three, but we’re often doing far more than the equivalent of three full-time employees. That’s down to how we're able to leverage systems, data, and processes.
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Inside VitaMoment’s Journey to KPI-Driven Growth and Data Ownership

We’ve always been a KPI-driven company. But we wanted to scale that mindset across every team member, every team, every decision.
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How Danish Endurance boosted profitability by 77 % and transformed data management with Weld

Before Weld, our data infrastructure was limited and we relied heavily on Excel files and custom Python scripts.
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Matias Voldby Drejer, BI Lead logo

How Female Invest centralized data management and saved resources with Weld

Weld has saved us a ton of time, from not having data ready to having a fully functional data warehouse and connectors.
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How Soundboks streamlined data integration with Weld, S3, and Databricks

By integrating Weld, Amazon S3, and Databricks, Soundboks built a modern data pipeline that automates data ingestion, improves reporting, and provides up-to-date visibility into sales performance
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Jens Karstoft, Chief Operating Officer at Roccamore logo

How Roccamore unlocked better business insights with Weld

We didn’t have a good data setup, so we lacked the business insights we needed. Weld has allowed us to set up a structured data infrastructure and access insights quickly.
Jens Karstoft, Chief Operating Officer at Roccamore

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