Talend vs AWS Glue: Which ETL Tool Is Best for Your Data Stack?

Choosing the right ETL tool for data integration can be tricky, especially when comparing widely used solutions like Talend and AWS Glue.

Talend is known for its flexibility, rich connector library, and strong data quality features. AWS Glue, on the other hand, gives you a serverless experience with deep AWS integration and auto-scaling for big data workloads.

Both are powerful, but they serve different needs and come with their trade-offs.

If you are trying to decide which one fits your team, stack, goals, and budget best, this article will help you.

By the end of this article, you’ll have a clear understanding of how these tools compare, and in this Talend vs AWS Glue debate, which one wins for you.

What Is Talend?

G2 Rating: 4.4 (66)

Gartner Rating: 4.4 (74)

Talend is a Qlik-owned data integration platform. Beyond being a data ingestion tool, it lets you collect, transform, and cleanse data from virtually any source.

Talend Data Fabric, their flagship offering, combines ETL and ELT capabilities, data quality, and governance in one environment. It is best suited for high-volume, complex data workflows that demand flexibility, scalability, and control.

But why should you choose Talend?

Talend offers a low-code, drag-and-drop interface, real-time processing, and integration data quality features. It is an excellent fit for mid-sized to large organizations with dedicated data engineering teams. However, smaller teams might find it too feature-heavy.

Key features of Talend

• Connector coverage: Offers 1,000+ pre-built connectors for databases, cloud services, SaaS apps, and file systems.
• Data quality management: Includes profiling, cleansing, masking, and metadata management at each step.
• Real-time sync: Enables Change Data Capture (CDC) and streaming to keep data updated across systems with minimal delay.
• Flexible deployment: Supports on-premise, hybrid, and cloud-native environments across AWS, Azure, Google, etc.
• Scalable architecture: Uses Spark or Hadoop for big data processing, supporting petabyte-scale workloads.

Use cases

• Cloud data warehousing: Load and transform data into platforms like Snowflake, Redshift, or BigQuery.
• Data migration and consolidation: Move legacy data into modern cloud systems during infrastructure upgrades.
• Real-time data integration: Use CDC for up-to-date dashboards and operational reporting.
• Data quality and governance: Clean, validate, and govern data for standards compliance.

Pricing

Talend’s pricing is a custom subscription-based model structured into progressive tiers.

• Starter: Moves SaaS apps and database data to cloud data warehouses with basic quality and cataloging.
• Standard: Adds real-time CDC synchronization and broader connectivity with flexible deployment.
• Premium: Automates transformations, provides data warehouse & lakehouse automation, and includes lineage and Spark processing.
• Enterprise: Offers comprehensive quality, governance, and AI capabilities for trusted data products and Generative AI.

It offers a free 14-day trial for Talend Cloud.

Pros and cons

Pros

• Supports batch and real-time processing
• Automates reusable data creation
• AI and LLM extensibility in pipelines 

Cons

• Unclear pricing structure and high costs for enterprise features
• Steep learning curve
• Might be slow with large data sets

What Is AWS Glue?

G2 Rating: 4.3 (194)

Gartner Rating: 4.4 (479)

AWS Glue is Amazon’s fully managed, serverless solution for ETL (extract, transform, load) processes. It lets you discover, prepare, and integrate data with autoscaling and a low-code visual interface.

You can build jobs in Python or Scala, or use Glue Studio for ease of use. It also integrates with AWS ML services for machine learning pipelines.

Why choose AWS Glue ETL?

The AWS Glue architecture is serverless, removing the need to manage infrastructure. It is ideal for cloud-native teams already on AWS.

Key features of AWS Glue

• Serverless architecture: Provides a fully managed environment with auto-provisioning and scaling.
• Centralized data catalog and automated discovery: Maintains a persistent metadata repository for inferred schemas.
• Automated ETL code generation: Converts visual workflows into PySpark or Scala scripts.
• Deep AWS ecosystem integration: Offers 70+ connectors for AWS data sources and services like S3, Kinesis, SageMaker, and more.
• Flexible job scheduling: Allows job scheduling based on time, events, or task dependencies.

Use cases

• Cloud data warehousing: Transfer and transform data sourced from S3 for analytical use in Redshift or Athena.
• Machine learning preparation: Catalog and prepare data across AWS services for machine learning workflows.
• Data migration: Migrate on-premises data to AWS cloud storage and databases.
• Real-time streaming processing: Build event-triggered ETL pipelines using Kinesis and Glue.

Pricing

AWS Glue uses a pay-as-you-go pricing model based on resource consumption.

• ETL jobs and interactive sessions: Pricing based on Data Processing Unit (DPU) consumption, at $0.44 per DPU-hour, charged by the second with a 1-minute minimum.
• Data Catalog: The first million metadata objects and access requests are free monthly. Beyond this, you’re charged $1.00 per 100,000 objects and $1.00 per million requests.
• Crawlers: Charged $0.44 per DPU-hour with a 10-minute minimum.
• DataBrew: Interactive sessions are $1.00 per 30-minute session. DataBrew jobs are $0.48 per node hour.
• Data Quality: Priced at $0.44 per DPU-hour for recommendations, evaluations, anomaly detection, and model retraining.
• Zero-ETL: No base fee but charges $1.50 per GB for data ingestion compute resources.

Prices vary by region. AWS offers a free tier for specific Glue components.

Pros and cons

Pros

• Supports schema versioning and evolution.
• Provides built-in monitoring and alerting.
• Ensures enterprise-grade security.

Cons

• Limited support for non-AWS sources.
• Cold start latency.
• Costs are hard to predict.

Talend vs AWS Glue vs Hevo: A Detailed Comparison Table

Now that we have analyzed Talend and AWS Glue individually, let’s compare them along with Hevo, a popular Talend and AWS Glue alternative.

Here’s a table highlighting the key differences between the three data integration tools across various features.

This table shows Talend’s depth and flexibility, especially for teams looking for strong data governance and hybrid deployment.

AWS Glue, on the other hand, excels in serverless automation and is ideal for AWS-native stacks, focusing on scalability.

Where does Hevo stand as one of the AWS Glue and Talend alternatives?

Hevo offers no-code pipelines with broad connector coverage. It has the simplicity of Glue plus the completeness of Talend, without the complexity of either.

AWS Glue vs Talend: In-Depth Feature & Use Case Comparison

While the table gives you a brief overview of the differentiators in both the ELT tools, let’s get into it deeper so you can make a sound decision.

Connectivity integrations

Talend: Provides 1,000+ prebuilt connectors, including SaaS apps, databases, cloud platforms, APIs, and file systems. It is an open-source ETL tool that supports batch and real-time integrations across hybrid environments.

AWS Glue: Focuses heavily on AWS-native integrations like S3, RDS, and SageMaker. While it connects to other sources, coverage outside AWS is limited and often requires additional setup.

This gives Talend an edge for broader and more flexible integration options.

Talend Data Integration helps to collaborate between different services and helps in data ingestion from various sources like Azure, AWS, on-premises, etc. It supports almost all kinds of file types and there are very good data quality check features available in Talend.

Arijit C.

Data Engineer

Setup and maintenance

Talend: Requires installation, configuration, and often dedicated engineering resources to manage deployments, especially in hybrid or on-premises setups.

AWS Glue: It is serverless, which means you don’t need to manage any infrastructure. Once configured, it automatically handles provisioning, scaling, and monitoring.

The winner here is AWS Glue for ease of setup and ongoing maintenance.

I love how simple data management and organization are with it. AWS Glue saves a ton of time by automating most of the data integration and preparation process. Even for novices the visual interface is easy to use, and because it\'s serverless, I don\'t have to worry about infrastructure. The user interface is simple to use and navigate, making tasks straightforward.

Milan S.

Senior Data Analyst

Real-time streaming

Talend: Talend supports real-time processing through native CDC, message queues, and streaming APIs. It offers more control and customization.

AWS Glue: Handles real-time use cases with features like Glue Streaming ETL and integration with Kinesis, but it’s more tuned for batch or scheduled jobs.

If your priority is real-time streaming, Talend is a better choice.

Data transformation capabilities

Talend: Provides a drag-and-drop visual interface through Talend Studio, making complex transformations easier. It also supports custom code like Java and SQL for advanced scenarios.

AWS Glue: Offers Glue Studio, a visual builder for Spark ETL jobs. It auto-generates PySpark or Scala code, which you can customize for more intricate transformations.

Both offer strong visual tools that are adaptable for custom code transformations.

As per my experience, Talend Cloud Data Integration is among the industry leaders in Integration tools available in the market. It offers so many great features, connectors, and transformation components, which are very user-friendly, and it is a low-code tool.

Verified User

Data Analyst

Its a fully managed tool that is serverless. Glue offers a visual interface and code generation capabilities for data preparation and ETL (Extract, Transform, Load) tasks. You can visually design data transformation workflows or write custom code in Python or Scala using Apache Spark, simplifying the process of transforming and cleaning your data.

Anjali J.

Lead Data Engineer

Pricing

Talend: Follows a subscription-based model and can scale up with added features and users, but it gets expensive with enterprise features.

AWS Glue: Follows a pay-as-you-go model based on DPU usage. This can be helpful for teams with predictable usage, but it can be expensive if not monitored correctly.

It’s a tie. Talend’s predictable upfront costs work better if you are working with larger data sets consistently with fixed budgets. However, AWS Glue is a much more affordable option for workloads that run occasionally or vary in size.

When to Choose Talend?

Choose Talend if your team needs a flexible, enterprise-grade platform that handles complex data pipelines across hybrid or multi-cloud environments.

It is particularly a better choice if data quality, governance, and broad connector coverage are your priorities.

Its robust real-time data synchronization capabilities position it as a strong contender and it often sparks a Fivetran vs Talend discussion for continuous data movement as well.

If you are managing high-volume, real-time, or compliance-heavy workflows, Talend offers the depth and control to meet those demands.

When to Choose AWS Glue?

Choose AWS Glue if your data infrastructure is AWS-centric and you seek a fully managed, serverless ETL solution.

It’s ideal for teams looking to automate data pipelines without worrying about provisioning or scaling. The AWS Glue features work best when your sources and destinations are within the AWS ecosystem, and you are comfortable working with Spark or PySpark.

It also offers flexibility and cost control for variable or scheduled workloads, making it an excellent fit for cloud-native teams that need scalable processing without managing infrastructure. If you are ready to take the leap, an AWS Glue tutorial is a great next step.

Why Does Hevo Stand Out?

Hevo strikes the right balance between ease of use and powerful functionality. It offers fully automated, no-code pipelines with automatic schema mapping, real-time data syncing, and support for both pre-load (ETL) and post-load (ELT) transformations.

Unlike Talend’s heavy setup or AWS Glue’s lock-in, Hevo works out of the box across 150+ connectors with multiple cloud environments. You get granular pipeline visibility, multi-region support, and built-in data integrity checks at every stage without any custom coding.

Its predictable, subscription-based pricing avoids the guesswork, surprise costs, or scaling concerns. Hevo brings the best of both worlds in one single platform.

All of this makes it the perfect choice for teams that want speed, reliability, and scale without the overhead.

Want to try it yourself? Sign up for Hevo’s 14-day free trial.

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