Stitch vs AWS Glue: Which Data Integration Tool Fits Your Workflow Best

Many teams feel stuck when choosing the right ETL tool for their growing data stack. You may want something simple and reliable with minimal maintenance, or you may look for something that provides flexibility with code.

Stitch vs AWS Glue is a common comparison because both tools reliably move data, but serve different needs. Stitch offers an easier approach while AWS Glue supports deep customization and scale.

This guide explains each tool in detail, including their features, pricing, limitations, strengths, and ideal use cases. By the end, you will know which option fits your workloads better and when it makes sense to consider a stronger alternative.

What Is Stitch?

G2 rating: 4.4 (68)

Gartner rating: 3.9 (3)

Stitch, now a part of Qlik, is a simple ELT tool that makes data replication efficient. It’s built for teams that want straightforward pipelines from SaaS apps and databases without managing infrastructure or complex integration logic.

The platform offers over 130 pre-built connectors that work out of the box and connect sources and warehouses, such as Salesforce and Snowflake. The ELT approach lets you transform your data in the warehouse using SQL or tools like dbt. This helps you focus on analysis rather than pipeline maintenance.

Key features of Stitch

• Singer framework: Provides an open-source standard for building and extending connectors, which allows you to add custom taps and targets whenever required.
• Row-level tracking: Offers row-by-row incremental replication visibility to verify data completeness, catch discrepancies early, and troubleshoot pipeline issues.
• Selective sync: Enables fine-grained control over which tables and columns move to the warehouse, which reduces data volume, protects sensitive fields, and manages costs.
• Schema drift handling: Detects structural changes at the source and updates the warehouse schema automatically, so pipelines continue running without manual adjustments.
• Multi-table syncs: Helps coordinate multiple tables within a single extraction job and ensure that related data moves in a consistent and predictable sequence.

Use cases

• Sales pipeline visibility: Sync CRM objects like leads and activities into Snowflake to give sales teams an up-to-date view of customer movement through the funnel.
• Historical audit logging: Archive off-site, long-term copies of all transaction logs in a secure cloud warehouse to meet strict financial or regulatory requirements.
• BI-focused replication: Replicate production databases into analytics warehouses so teams can run BI queries without touching live systems.

Pricing

Stitch offers a tiered pricing structure.

• Standard: Starts at $100/month for up to five million rows, one destination, and access to 10 standard sources for five users.
• Advanced: $1,250/month for 100 million rows, three destinations, and unlimited users.
• Premium: $2,500/month for one billion rows, five destinations, and unrestricted sources and users.

Since joining Qlik, Stitch now directs new customers toward Qlik Talend Cloud, which provides a 14-day free trial.

Pros and cons

Pros:

• Low barrier to launching new data projects quickly.
• All plans include SOC 2 Type II and ISO 27001 compliance.
• Simple monitoring dashboard for quick pipeline health checks.

Cons:

• Batch-focused syncing and limited CDC options.
• Connector quality depends on community development.
• Limited in-flight transformation capabilities.

What Is AWS Glue?

G2 Rating: 4.3 (194)

Gartner Rating: 4.3 (496)

AWS Glue is a serverless ETL service built for large-scale workloads inside the AWS ecosystem. It offers deep flexibility over data transformation, orchestration, and schema management. 

You can build complex data pipelines that handle petabytes of information. AWS Glue is noted for its deep integration with core AWS services like S3, Redshift, and Athena. This makes it ideal for advanced engineering teams who require granular control over their pipelines.

Key features of AWS Glue

• AWS Glue Data Catalog: Provides a centralized and serverless metadata repository that stores details across sources and enables unified querying with Athena, Redshift, and EMR.
• Custom job scripting: Helps write Apache Spark transformations in Python or Scala with access to AWS Glue DynamicFrame APIs for schema flexibility and pushdown predicates.
• Event-driven triggers: Starts Glue jobs automatically based on S3 events, CloudWatch schedules, or custom applications for real-time ETL execution.
• Workflow orchestration: Enables the automation and sequencing of multiple ETL jobs and triggers, so complex pipelines run reliably without manual intervention.
• AWS Glue DataBrew: Provides a visual data preparation tool with more than 250 pre-built transformations, so that analysts can clear and normalize data without coding. 

Use cases

• Data lake consolidation: Combine structured and semi-structured datasets from multiple S3 buckets into a unified data lake for analytics teams to query easily.
• IoT stream processing: Aggregate sensor or device data from Kinesis streams and load it into analytics warehouses for real-time monitoring and alerts.
• Cross-account data sharing: Consolidate datasets from multiple AWS accounts into a single warehouse for centralized analytics across business units.

Pricing

AWS Glue’s pricing is based on resource consumption.

• ETL jobs and interactive sessions: Charged per Data Processing Unit (DPU) at $0.44 per DPU-hour, billed per second with a 1-minute minimum.
• Data Catalog: First million metadata objects and access requests are free each month. Additional objects cost $1.00 per 100,000, and requests $1.00 per million.
• Crawlers: $0.44 per DPU-hour with a 10-minute minimum.
• DataBrew: $1.00 per 30-minute interactive session, jobs run $0.48 per node-hour.
• Data Quality: $0.44 per DPU-hour for recommendations, evaluations, anomaly detection, and model retraining.
• Zero-ETL: No base fee; data ingestion compute is $1.50 per GB.

Prices differ by region, and AWS provides a free trial for certain Glue services.

Pros and cons

Pros:

• Highly secured through native AWS IAM roles.
• Automatic partitioning of output data.
• Job bookmarks track processed data and avoid duplicate loads.

Cons:

• Steep learning curve for complex workflows.
• Limited support outside the AWS Glue architecture.
• Costs can escalate quickly when job configurations are inefficient.

Stitch vs AWS Glue vs Hevo: A Detailed Comparison Table

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

Ease of use and maintenance

Stitch is ideal for quick data projects because it handles the complexities of schema management automatically. You can launch initial pipelines in mere minutes using its intuitive interface. This lets your BI analysts move data efficiently without relying on engineering teams.

Conversely, AWS Glue ETL requires deep familiarity with the AWS console, IAM roles, and coding in PySpark to set up and monitor. If you need to debug a job or alter a pipeline, an experienced data engineer must step in.

When it comes to ease and simplicity, Stitch offers a noticeably easier experience.

Stitch:

Stitch is an easy tool to include ETL from sources into your data warehouse. Set up is really easy to do, and its low maintenance, which helps in small data teams.

Verified User

Connector coverage and extensibility

Stitch has the upper hand in terms of the number and simplicity of pre-built SaaS API connectors. It lets you build custom taps through Singer, which helps when your tools are spread across different vendors. However, these connectors rely on you for maintenance.

AWS Glue offers greater depth when integrating with core AWS services like S3, Redshift, and Athena. You can access AWS Glue tutorials for detailed guides focused on these deep cloud integrations.

The better tool depends on your use case. AWS Glue works better when your stack already sits inside AWS because its integrations then feel smoother. Stitch is a better option for quick SaaS ingestion.

Stitch:

Stitch integrates with most large companies such as Google Ads, Microsoft Ads, etc. One of the best things is that it sets up cost allocation in a very easy straightforward manner.

Megan S.

Digital Marketing Director

Transformation flexibility

Stitch keeps transformations simple. Most of the work happens after the data reaches your warehouse, so you rely on SQL for modeling rather than complex scripting. This suits smaller teams that want clean control at the warehouse layer.

AWS Glue gives you full ETL power before the load step by using Spark for advanced logic, PII handling, and rule-based data cleanup. You get more structure and depth if you need heavy engineering oversight.

If transformation is your priority, AWS Glue’s features give you much more control and enterprise support.

Real-time streaming capabilities

Stitch focuses on batch replication with optional CDC for certain databases, which is enough when your workloads refresh at predictable intervals. However, it is not built for continuous pipelines or heavy streaming demands.

AWS Glue helps you manage large volumes of real-time data using Spark Structured Streaming with Kinesis or Kafka. This creates a smooth path for continuous ingestion and transformation.

If low latency or event-driven data matters to you, AWS Glue performs more efficiently.

Pricing transparency and affordability

Stitch offers a predictable pricing option compared to other alternatives, which helps when you want clarity on recurring costs and do not want to micromanage resource usage. You get stable monthly billing that stays easy to forecast as your pipelines grow.

AWS Glue works well when your jobs are tuned carefully because you only pay for compute time, although inefficient scripts can drive up your bill quickly.

Both can be cost-effective, but Stitch offers greater simplicity while AWS Glue provides tighter engineering control.

Stitch:

Stitch is totally self-serve, there's no relationship with account managers or customer success representatives needed. You can manage your entire ETL system from their UI. For the price and convenience, Stitch is amazing. I believe we've saved approximately $60k/year by using Stitch over one of their competitors that we initially talked to.

Tom J.

Data Engineer and Analyst

AWS Glue:

With AWS Glue, you only pay for the resources you use during data processing. It provides cost optimisation features like data compression and partitioning, helping to reduce storage and processing costs.

APOORV G.

Software Engineer

View Review

When to Choose Stitch

Stitch makes sense for small teams using popular SaaS tools. You don’t have to wrestle with custom integrations or write long scripts to get data flowing. The platform gives you a straightforward ingestion path and saves you time you’d otherwise spend stitching together workarounds.

Choose Stitch when predictability matters more than unlimited customization. Its pricing structure remains consistent with how your data loads each day. If you value stability and clarity over real-time streaming, Stitch can be a safer and more comfortable choice.

When to Choose AWS Glue

Choose AWS Glue if you are already an AWS user or are planning to migrate. You need to have data engineering resources and a team that is comfortable with Spark, Python, and Scala. It is a promising choice if you are looking to scale your pipelines while dealing with sporadic data volumes. The compute-based pricing model makes it cost-effective.

If you are an enterprise, the serverless model eliminates operational burden. However, consider AWS Glue alternatives if you need extensive SaaS connectors or want to avoid vendor lock-in for future migrations. The learning curve and setup effort make sense only for complex use cases.

Why Does Hevo Stand Out?

Hevo is a flexible and scalable option compared to Stitch and AWS Glue. It gives you the ease of a no-code solution while supporting growing data volumes.

Here’s how Hevo differentiates itself:

• Battle-tested connectors: Offers 150+ pre-built integrations across SaaS tools, databases, and cloud storage, with custom connectors built and maintained for you.
• No-code with depth: Helps you build production-ready pipelines visually, while still retaining the option to use SQL and Python for customization.
• Always-on reliability: Automatic retries, real-time error detection, and intelligent load handling ensure your data stays accurate and up to date.
• Auto-scaling: Adjusts resources instantly as your traffic spikes, thereby eliminating the manual tuning and ‘worker’ configuration required by tools like AWS Glue.
• Clear costs: Predictable pricing starts at $239/month with a free tier option to explore the platform.
• Human assistance: Provides a 24/7 support team that helps you launch, troubleshoot, and scale pipelines without delays.

In short, Hevo works best when you want secure real-time pipelines without worrying about surprise costs.

Want to try it for yourself? Book a free demo today!

FAQs