As businesses increasingly rely on data from multiple sources, SaaS ETL tools have become essential to modern data infrastructure, simplifying how companies move and connect data across systems.
Think about it: how do you transfer data smoothly when it’s scattered across multiple apps and platforms?
Most teams face ETL challenges like inconsistent formats, scaling complexities, or maintaining accuracy. SaaS tools solve these problems by removing heavy setup and making the data integration vs ETL question much easier to handle.
In this article, we’ll look at the 12 best SaaS ETL tools to consider in 2025, highlighting their features and how they tackle real-world issues. You’ll see how they stack up and which ones suit different business needs.
And if you’re short on time, we’ve shared our quick pick of the top 3 tools right at the start.
Table of Contents
What are SaaS ETL Tools?
SaaS ETL tools are cloud-based platforms that extract data from applications, standardize it, and load it into your warehouse or analytics system. With pre-built connectors for services like Salesforce, HubSpot, and Google Analytics, they remove the need for manual exports or complex coding, making data integration simple and infrastructure-free.
The key features of SaaS ETL tools include
- automated data sync to remove manual work,
- real-time or scheduled transfers to keep analytics up to date, and
- built-in transformations to clean and standardize data.
They unify information from multiple SaaS apps into a single source of truth for accurate reporting and insights, while offering monitoring, error handling, and scalable processing to match growing data needs.
Top 12 SaaS ETL Tools
Below is the overall comparison of the top 12 SaaS ETL Tools:
Tool | Best For | Pricing | Real-time Support | Pre-built Connectors | Deployment |
Hevo | Mid-market teams | Starts at $299/month | Yes | 150+ | Cloud |
Fivetran | Enterprise | Starts at $120/month | Yes | 300+ | Cloud |
Airbyte | Open-source flexibility | Free, Cloud from $100/month | Limited | 300+ | Cloud/Self-hosted |
Stitch | Small businesses | $100-$1,250/month | Yes | 130+ | Cloud |
Zapier | Simple automations | Free, paid from $19.99/month | Yes | 5000+ | Cloud |
Microsoft Power Automate | Microsoft ecosystem | $15/user/month | Yes | 400+ | Cloud |
Integromat/Make | Visual workflows | Free, paid from $9/month | Yes | 1000+ | Cloud |
Pentaho | Complex transformations | Contact for pricing | No | 100+ | On-premise/Cloud |
Talend | Data governance | $100-$2,500+/month | Yes | 900+ | Cloud/On-premise |
IBM DataStage | Enterprise processing | Contact for pricing | Yes | 200+ | On-premise/Cloud |
Informatica | Large enterprises | Contact for pricing | Yes | 500+ | Cloud/On-premise |
AWS Glue | AWS ecosystem | $0.44/DPU-hour | Yes | Limited | Cloud |
1. Hevo
Hevo Data is a no-code data pipeline platform designed for marketing teams, sales operations, and data analysts who need reliable SaaS data integration without technical complexity. It specializes in connecting popular business applications like Salesforce, HubSpot, and Google Analytics to modern data warehouses and databases with minimal setup time.
Hevo automates data extraction, transformation, and loading from 150+ SaaS sources, helping marketing teams unify campaign data, sales teams centralize CRM information, and analysts create comprehensive reporting dashboards. Hevo’s strength lies in its ability to handle schema changes automatically and provide data consistency across different source formats.
What makes Hevo unique is its focus on business user experience with automatic schema mapping, pre-built transformations for common use cases, and intelligent error handling that maintains data flow continuity.
Key Features:
- Auto-schema detection handles source changes without breaking pipelines
- The visual transformation editor allows business users to create custom data rules
- Real-time monitoring with alerts for pipeline health and data quality issues
- Incremental data loading reduces processing time and costs
Pros:
- Easy setup
- Reliable data delivery
- Excellent customer support
- Transparent pricing
Cons:
- Limited advanced transformation capabilities
- Fewer enterprise governance features
Pricing:
- Free plan: Up to 1 million events monthly with basic connectors
- Starter plan: $239/month for 5 million events with essential features
- Professional/Business: $599+ for 20+ million events with advanced capabilities
2. Fivetran
Fivetran is a fully managed SaaS ETL platform that automates data replication from 300+ sources into data warehouses. It specializes in enterprise-grade data integration with zero-maintenance pipelines for organizations handling high-volume data flows.
The platform operates on a set-and-forget principle, automatically managing schema changes, API updates, and data transformations. Built for enterprise data teams requiring reliable, scalable infrastructure without technical overhead.
The platform eliminates manual ETL work by automatically handling schema drift and API changes across all connected SaaS applications. Pre-built connectors manage authentication, rate limiting, and incremental updates without requiring coding or maintenance from your team.
It ensures enterprise-grade reliability with SLA guarantees, robust monitoring, and compliance features for regulated industries. Choose Fivetran when you need hands-off data operations that scale without expanding your engineering resources.
Key Features:
- Automatic connector maintenance and API updates
- Advanced data governance with lineage tracking
- Enterprise-grade security certifications
- Column-level incremental sync for large datasets
Pros:
- Enterprise reliability
- Extensive connector library
- Excellent uptime
Cons:
- Expensive pricing model
- Limited transformation capabilities
- Connector-based costs
Pricing:
- Free plan: Up to 500,000 Monthly Active Rows (MAR) with 5,000 transformation runs monthly
- Standard plan: Per-connector MAR billing starting around $500 per million MAR (varies by plan tier)
- Enterprise/Business Critical: Custom pricing with volume discounts, typically $700-$2,667/month for 2M+ MAR usage
3. Airbyte
Airbyte serves organizations wanting open-source flexibility with the option to customize connectors and maintain full control over their data infrastructure while keeping costs predictable.
Key Features:
- Open-source with self-hosting options
- Custom connector development framework
- Community-contributed connectors
- Docker-based deployment flexibility
Pros:
- Cost-effective
- Customizable
- Large connector ecosystem
Cons:
- Requires technical expertise
- Limited enterprise support
- Basic UI
Pricing:
- Open-source: Completely free with unlimited connectors and data volume
- Cloud plan: Starts at $10/month with additional credits at $2.50 per credit
- Enterprise: Custom pricing with advanced security and dedicated support
4. Stitch
Stitch appeals to small to mid-sized businesses needing straightforward SaaS data integration with simple row-based pricing and quick implementation for common analytics use cases.
Key Features:
- Row-based pricing transparency
- Singer tap ecosystem compatibility
- Basic transformation capabilities
- Integration with popular BI tools
Pros:
- Simple pricing
- Quick setup
- Good for small teams
Cons:
- Limited transformation features
- Basic monitoring
- Fewer enterprise connectors
Pricing:
- Standard: $100/month for 5 million rows with 15-minute refresh intervals
- Advanced: $1,250/month for 100 million rows with faster sync frequencies
- Premium: $2,500+/month for enterprise features and priority support
5. Zapier
Zapier focuses on business process automation rather than traditional ETL, connecting SaaS applications for workflow automation and simple data synchronization between business tools.
Key Features:
- Trigger-based automation workflows
- Extensive app ecosystem (5000+ apps)
- Multi-step workflow creation
- Built-in filters and formatters
Pros:
- Massive app library
- User-friendly interface
- Great for automations
Cons:
- Not designed for analytics
- Limited data transformation
- Expensive for high volume
Pricing:
- Free: 100 tasks monthly with 2-step workflows
- Starter: $19.99/month for 750 tasks and multi-step automation
- Professional/Team: $49-$69/month with unlimited premium apps and shared workspaces
6. Microsoft Power Automate
Microsoft Power Automate is designed for organizations heavily invested in the Microsoft ecosystem, providing seamless integration between Office 365, Dynamics, and third-party SaaS applications. It excels at connecting Microsoft tools with external platforms for unified business processes.
The platform helps IT departments automate workflows while maintaining enterprise security standards and compliance requirements within familiar Microsoft interfaces. Power Automate stands out with its deep integration into Microsoft’s productivity suite and robust enterprise governance features.
Key Features:
- Native integration with Microsoft 365 and Azure services
- AI-powered process automation with cognitive services
- Enterprise-grade security and compliance controls
- Visual workflow designer with pre-built templates
Pros:
- Deep Microsoft integration
- Enterprise security
- Familiar interface for Microsoft users
Cons:
- Limited non-Microsoft connectors
- Expensive for high-volume scenarios
Pricing:
- Per user: $15/month for standard connectors and cloud flows
- Per flow: $100/month for unlimited runs of specific automated processes
- Premium connectors: Additional $40/month for advanced integrations like SAP and Oracle
7. Make (Integromat)
Make specializes in visual workflow automation for teams needing complex, multi-step data transformations between SaaS applications. It’s ideal for operations teams managing intricate business processes that require conditional logic and data manipulation.
The platform helps users create sophisticated automation scenarios without coding, supporting everything from simple data syncs to complex multi-app workflows. Make’s visual approach and powerful scenario builder make it unique for handling complex integration requirements.
Key Features:
- Visual scenario builder with drag-and-drop interface
- Advanced filtering and routing capabilities
- Real-time execution monitoring and debugging
- Support for complex conditional logic and loops
Pros:
- Powerful visual editor
- Flexible workflow design
- Good transformation capabilities
Cons:
- Steep learning curve
- Complex pricing structure
- Limited enterprise features
Pricing:
- Free: 1,000 operations monthly with basic scenarios
- Core: $9/month for 10,000 operations with advanced features
- Pro/Team: $16-$29/month for higher operation limits and team collaboration
8. Pentaho
Pentaho targets technical teams requiring comprehensive data integration with advanced transformation capabilities for complex business intelligence projects. It’s best suited for organizations with dedicated data engineers who need extensive customization options.
The platform helps enterprises handle large-scale data processing with sophisticated transformation logic, supporting both traditional ETL and modern data lake architectures. Pentaho’s strength lies in its powerful transformation engine and extensive connectivity options.
Key Features:
- Advanced data transformation and cleansing capabilities
- Support for big data processing with Hadoop integration
- Comprehensive data quality and profiling tools
- Extensive metadata management and lineage tracking
Pros:
- Powerful transformation engine
- Supports complex data processing
- Good for big data
Cons:
- Requires technical expertise
- Steep learning curve
- Limited cloud-native features
Pricing:
- Community Edition: Free open-source version with basic ETL capabilities
- Enterprise: Subscription-based licensing starting around $500/month per server
- Cloud: Custom pricing based on data volume and processing requirements
9. Talend
Talend serves enterprises needing comprehensive data governance and quality management across their entire data landscape. It’s designed for data teams managing complex compliance requirements and data lineage tracking.
The platform helps organizations maintain data quality standards while connecting hundreds of data sources with robust governance controls. Talend’s unique value lies in its comprehensive data fabric approach and strong governance capabilities.
Key Features:
- Comprehensive data governance and quality management
- Self-service data preparation for business users
- Advanced data lineage and impact analysis
- Machine learning-powered data quality suggestions
Pros:
- Strong governance features
- Comprehensive platform
- Good data quality tools
Cons:
- Complex implementation
- Expensive licensing
- Requires technical resources
Pricing:
- Open Studio: Free community version with core data integration features
- Cloud Starter: $1,170/month for basic cloud data integration and management
- Enterprise: $2,500+/month for advanced governance, security, and support
10. IBM DataStage
IBM DataStage is built for large enterprises requiring high-performance, parallel processing of massive data volumes with enterprise-grade reliability. It excels in mission-critical environments where data processing speed and reliability are paramount.
The platform helps enterprises handle complex data integration scenarios with a sophisticated parallel processing architecture and robust error handling. DataStage stands out with its proven enterprise scalability and advanced parallel processing capabilities.
Key Features:
- Massively parallel processing architecture
- Advanced job scheduling and dependency management
- Comprehensive data quality and standardization tools
- Enterprise-grade monitoring and performance optimization
Pros:
- Excellent performance for large volumes
- Enterprise reliability
- Strong parallel processing
Cons:
- Expensive licensing, complex setup
- Requires specialized skills
Pricing:
- Perpetual license: $25,000+ one-time cost plus annual maintenance fees
- Subscription: Monthly licensing based on processing capacity and user count
- Cloud Pak for Data: Bundled pricing with other IBM data platform services
11. Informatica
Informatica targets large enterprises needing a comprehensive data management platform with advanced AI-driven capabilities and enterprise governance. It’s ideal for organizations with complex data landscapes requiring sophisticated master data management and data governance.
The platform helps enterprises achieve unified data management across cloud and on-premise environments with AI-powered data discovery and quality management. Informatica’s uniqueness lies in its AI-driven automation and comprehensive enterprise data management capabilities.
Key Features:
- AI-powered data discovery and cataloging
- Comprehensive master data management
- Advanced data governance and privacy controls
- Cloud-native architecture with hybrid deployment options
Pros:
- Comprehensive platform
- AI-powered features
- Strong enterprise support
Cons:
- Very expensive
- Complex implementation
- Requires significant resources
Pricing:
- Cloud Data Integration: Usage-based pricing starting around $2,000/month
- PowerCenter: License-based pricing typically $50,000+ for enterprise deployments
- Intelligent Cloud Services: Credit-based consumption model with flexible scaling
12. AWS Glue
AWS Glue is designed for organizations already invested in the Amazon Web Services ecosystem, providing serverless ETL processing that scales automatically. It’s perfect for companies using AWS data services who want native integration without managing infrastructure.
The platform helps teams build and run ETL jobs without server management while integrating seamlessly with other AWS analytics services. Glue’s serverless architecture and AWS ecosystem integration make it unique for cloud-first organizations.
Key Features:
- Serverless architecture with automatic scaling
- Native integration with AWS data services
- Visual ETL job designer and code generation
- Automatic schema discovery and data cataloging
Pros:
- No infrastructure management
- Seamless AWS integration
- Pay-per-use pricing
Cons:
- Limited to AWS ecosystem
- Fewer SaaS connectors
- Vendor lock-in
Pricing:
- Pay-per-use: $0.44 per Data Processing Unit (DPU) hour for ETL jobs
- Crawler: $0.44 per DPU-hour for automatic schema discovery
- Data Catalog: $1 per 100,000 requests plus $1 per 100,000 objects stored
What are the key factors in selecting the right ETL for SaaS?
1. Data Connector Availability
Pre-built connectors determine how quickly you can integrate popular SaaS platforms like Salesforce, HubSpot, Google Analytics, and Shopify without custom development work. The more native integrations available, the faster your deployment and lower your technical overhead.
Audit your current SaaS stack and prioritize ETL tools that support 80% of your critical applications out-of-the-box, while ensuring the provider regularly adds new connectors with a clear integration roadmap.
2. Real-time vs Batch Processing Capabilities
Processing capability determines whether your ETL tool handles immediate data updates (real-time) or scheduled chunks (batch processing). This choice is crucial for businesses needing up-to-the-minute reporting for sales dashboards, customer support, or marketing campaigns where delayed data impacts decision-making.
Identify which use cases require instant updates versus those that can wait for daily or hourly refreshes, and consider hybrid solutions offering both real-time streaming for critical data and batch processing for large historical datasets.
3. Data Transformation and Cleaning Features
Transformation capabilities standardize and clean raw SaaS data before it reaches your analytics platform, addressing inconsistent formats and varying data quality across different applications. Strong transformation features reduce the need for additional data preparation tools and ensure analytics-ready output.
Look for visual transformation editors that allow non-technical users to create cleaning rules without coding, plus essential features like data type conversion, field mapping, duplicate removal, and calculated fields.
4. Scalability and Performance
Your ETL solution must handle growing data volumes, increased sync frequencies, and additional data sources as your business expands. Poor performance leads to delayed reporting, failed syncs, and analytics bottlenecks, making scalability critical for protecting your investment.
Test the tool’s performance with expected data volumes during trial periods and choose cloud-native solutions that automatically scale processing power based on demand rather than fixed-capacity alternatives.
5. Security and Compliance Standards
Security encompasses data encryption, access controls, audit trails, and adherence to regulations like GDPR, SOC 2, and HIPAA. Since SaaS data often contains sensitive customer information and business intelligence, robust security practices prevent data breaches, regulatory penalties, and customer trust issues.
Verify the ETL provider meets your industry’s specific compliance requirements and offers features like data masking, role-based access controls, and comprehensive audit logging.
Try Hevo as Your Go-To SaaS ETL Solution
A solid SaaS ETL tool is key to running a smooth ETL workflow. While other platforms may give partial benefits, they often leave gaps that require extra effort to manage. Following ETL best practices means having a tool that is automated, reliable, and easy to scale, without heavy setup or ongoing maintenance. This is why picking the right solution is so important for any data-driven team.
That’s where Hevo sets itself apart. Instead of piecing together complex setups, Hevo delivers a fully managed, no-code ETL workflow designed to move data in real time across 150+ sources and popular warehouses like Snowflake, Redshift, and BigQuery. By combining automation with ETL best practices, Hevo helps you spend less time fixing pipelines and more time using data to drive insights and decisions.
To sum up, if you want a secure, modern data pipeline tool that simplifies ETL practices, sign up for Hevo’s 14-day free trial and see how it powers your modern data infrastructure.
FAQs
1. How does data integration from SaaS help to a data warehouse?
It centralizes and harmonizes data from various SaaS apps into one system, enabling faster decisions, accurate reporting, and improved business insights by eliminating silos and manual effort.
2. Which data can you extract from SaaS?
Data extracted includes customer records, sales and marketing metrics, user behavior, financial transactions, and operational logs from platforms like Salesforce, HubSpot, and Google Analytics.
3. How to start pulling data in minutes from SaaS (Hevo pitch) ?
Hevo offers quick setup with no coding, automated pipelines, and ready connectors for popular SaaS tools, letting users begin extracting and loading data to their warehouse in minutes.