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Trusted by 1,100+ data and ops teams saving millions of IT tickets with Integrate.io
Hevo and AWS Glue are both popular choices in the ETL space. Below is a detailed, side-by-side comparison of their capabilities, pricing, support, and security to help you decide which fits your data stack.
Hevo offers 150+ pre-built connectors for SQL, NoSQL, and SaaS sources including popular platforms like Salesforce, HubSpot, and Google Analytics
AWS Glue offers 100+ data sources including Amazon S3, DynamoDB, RDS, Redshift, and third-party systems
| Capability | Hevo | AWS Glue |
|---|---|---|
| Data loading | Handles high-volume data loading with automated retry mechanisms and error handling. Optimized for warehouse destinations like Snowflake, BigQuery, and Redshift. Loading is efficient but focused mainly on analytics use cases rather than operational systems. | Optimized for AWS targets like S3 and Redshift but limited flexibility for multi-cloud or hybrid environments |
| Data ingestion | Offers 150+ pre-built connectors for SQL, NoSQL, and SaaS sources with automated schema detection and management. Handles real-time CDC from databases and streaming sources, but requires technical setup for custom connectors beyond their catalog. Strong for standard sources, limited flexibility for unique data formats. | Connects to 100+ data sources but requires AWS ecosystem lock-in and complex configuration for non-AWS sources |
| Data transformation | Features no-code transformation capabilities with pre-built functions for common data operations. Transformations happen during the pipeline process, but complex business logic and custom transformations require technical expertise or workarounds. | Code-heavy approach requires Spark expertise and lacks visual, no-code transformation capabilities |
| Data replication | Provides automated, fault-tolerant replication with 100% data accuracy guarantees and built-in monitoring. Supports incremental sync and CDC for most major databases. However, replication is primarily one-way and lacks the bidirectional sync capabilities needed for operational workflows. | Serverless scaling handles large volumes but lacks real-time sync capabilities and granular scheduling options |
| Orchestration | Provides basic pipeline scheduling and monitoring with dependency management between data flows. Orchestration is straightforward for linear ETL workflows but lacks the sophisticated workflow automation needed for complex business process integration. | Pay-per-use billing can become unpredictable at scale with limited workflow automation for business users |
| Alerts and monitoring | Standard monitoring dashboard with basic alerts, but limited customization for complex notification workflows or advanced observability | CloudWatch integration provides basic monitoring but lacks granular pipeline observability and proactive failure detection |
| Dev QA account | No dedicated development or QA environment separation - testing and production changes happen in the same workspace | Development endpoints available but billed hourly with no clear separation between dev, staging, and production environments |
| AI workflows | Basic automation features but lacks dedicated AI-powered workflow optimization or intelligent pipeline management capabilities | Basic generative AI assistance for ETL authoring and Spark job modernization, but AI capabilities are narrow and AWS-centric |
| API | Limited API access for custom integrations, though primarily focused on pre-built connectors rather than extensive API-first development workflows | Limited programmatic access through AWS SDK and CLI, but lacks dedicated API for pipeline management or custom integrations outside AWS ecosystem |
| Source control | No built-in version control or Git integration for pipeline configurations, making collaboration and rollback challenging | No native version control or Git integration - relies on external AWS CodeCommit or third-party solutions for pipeline versioning |
Hevo
Usage-based pricing starting at $299/month with pay-per-event model - you only pay for successfully loaded data events, which can create unpredictable costs as data volumes scale. No transparent pricing tiers or fixed-fee options for budget planning.
AWS Glue
Pay-as-you-go billing by the second or minute with charges for ETL jobs, crawlers, Data Catalog storage and requests, DataBrew sessions, and Data Quality tasks. Development endpoints billed hourly. Costs vary by AWS Region with potential for unpredictable scaling expenses.
| Hevo | AWS Glue | |
|---|---|---|
Time to implement | Hevo typically requires 2-4 weeks for initial implementation, depending on data source complexity and transformation requirements. Simple connector setups can be completed in days, but custom transformations and complex data mappings often extend timelines. Their no-code approach helps accelerate deployment, though teams may need additional time for testing and validation. | Weeks to months for production-ready pipelines. Requires AWS infrastructure knowledge, Spark/Python coding skills, and time to configure security policies. Simple jobs may start quickly, but enterprise deployments need significant setup and testing. |
Onboarding | Hevo offers a self-service onboarding experience with guided tutorials and pre-built templates for common use cases. While they provide documentation and video walkthroughs, the initial setup process can be complex for teams without prior ETL experience. Enterprise customers receive dedicated onboarding sessions, but smaller teams often rely on trial-and-error learning. | Requires AWS expertise and infrastructure setup. Teams need to configure IAM roles, set up development endpoints, and understand Glue's serverless architecture before building first pipeline. Getting started involves learning AWS-specific concepts like crawlers, classifiers, and the Data Catalog structure. |
Support | Hevo provides 24/7 support through chat, email, and phone, with dedicated customer success managers for enterprise accounts. Their support team includes data engineers who can assist with pipeline troubleshooting and optimization. However, support quality can vary based on plan tier, with basic plans receiving limited technical guidance compared to enterprise offerings. | Relies on AWS support tiers and community forums. No dedicated data integration specialists. Support quality depends on your AWS support plan level, with basic plans offering limited technical guidance for complex ETL scenarios. |
Hevo
Hevo maintains SOC 2 Type II compliance and offers data encryption in transit and at rest. They provide GDPR compliance features and support for various data residency requirements. However, their security documentation can be limited compared to enterprise-focused platforms, and some advanced compliance features require higher-tier plans.
AWS Glue
Inherits AWS security model with comprehensive certifications. Offers VPC isolation, encryption at rest and in transit, and IAM integration. However, security configuration complexity requires dedicated AWS security expertise to implement properly.
Integrate.io combines ETL, Reverse ETL, and iPaaS in a single platform with fixed pricing at $1,999/month. No usage-based surprises, no tool sprawl.
FAQ
Clear answers to the questions teams ask when evaluating Integrate.io.
Still have questions?
Talk to an expert →Hevo is a no-code ETL platform with 150+ connectors built for loading analytics data into warehouses. AWS Glue is a serverless, code-heavy service optimized for AWS targets like S3 and Redshift, requiring Spark expertise and AWS ecosystem knowledge. Integrate.io unifies ingestion, transformation, warehousing, and Reverse ETL in one no-code platform that works across clouds with fixed-fee pricing.
Hevo starts at $299/month on a pay-per-event model, so costs scale with loaded events. AWS Glue bills pay-as-you-go by the second or minute across ETL jobs, crawlers, catalog storage, and hourly development endpoints, which can become unpredictable at scale. Integrate.io charges a fixed fee regardless of volume, keeping spend steady.
Hevo is no-code, though its onboarding can be complex for teams without ETL experience. AWS Glue requires AWS expertise, Spark or Python coding, and configuration of IAM roles and the Data Catalog before building a first pipeline. Integrate.io is no-code with hands-on human onboarding, so analysts and ops teams can build pipelines without coding or AWS-specific setup.
Hevo typically needs 2 to 4 weeks for initial setup, with simple connectors ready in days. AWS Glue can take weeks to months for production-ready pipelines because it requires AWS infrastructure knowledge, coding skills, and security policy configuration. Integrate.io offers fast setup with hands-on onboarding, so it launches quickly without deep infrastructure work.
Hevo is no-code but leans one-way and analytics-focused, while AWS Glue is powerful but code-heavy and locked into the AWS ecosystem with limited multi-cloud flexibility. Neither is built for business users to push data back to operational tools. Integrate.io adds no-code transformation, CDC, and Reverse ETL across clouds, so data moves in both directions without Spark or AWS lock-in.
Integrate.io replaces Hevo and AWS Glue with one unified data delivery platform.