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Blogs › MySQL ETL Tools
September 7, 2026  •  24 mins

12 Best MySQL ETL Tools to Build Reliable Data Pipelines in 2026 

Compare the 12 best MySQL ETL tools in 2026, by use case, setup complexity, pricing, and pipeline reliability. Find the right fit for your data stack.

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Mohsin
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12 Best MySQL ETL Tools to Build Reliable Data Pipelines in 2026 

Trusted by 2,000+ companies worldwide

Key Takeaways

The best MySQL ETL tool depends on your team's technical expertise, maintenance capacity, and need for real-time synchronization, governance, or scale.

  • No-code / managed ELT
    • Hevo Data: Real-time CDC via MySQL binlog, no-code setup, auto-healing schema handling, and built-in transformations.
    • Fivetran: Fully managed ELT with automatic schema updates and hands-free pipeline maintenance. Confirm current MAR-based pricing before committing.
  • Low-code / visual ETL
    • Integrate.io: Visual data preparation with 140+ connectors, supporting ETL, ELT, and reverse ETL.
    • Matillion: Cloud-native ELT for teams running large-scale transformations across Snowflake, BigQuery, and Redshift.
  • Enterprise ETL platforms
    • Qlik Talend Cloud: 900+ connectors, data lineage, and compliance-focused security for enterprise environments.
    • Pentaho PDI: Visual ETL with strong MySQL support and built-in error handling for governance-heavy and on-premises environments.
  • Developer-grade and open-source tools
    • Airbyte: Open-source ELT with 600+ connectors and log-based CDC, offering flexibility with additional DevOps requirements for self-hosting.
    • dbt: A transformation layer that pairs with tools such as Hevo, Airbyte, or Stitch for the transformation stage of ELT, but does not extract or load MySQL data itself.

MySQL is one of the world's most widely used relational databases, but moving data into and out of it at scale isn't always simple. The right ETL tool automates replication, adapts to schema changes, and keeps data flowing reliably across warehouses, SaaS applications, and operational systems. The wrong one leaves you troubleshooting failed syncs, managing brittle pipelines, and struggling to scale.

This guide compares 12 MySQL ETL tools across four categories: no-code managed ELT platforms, low-code ETL tools, enterprise integration platforms, and developer-focused open-source frameworks.

Our evaluation is based on connector coverage, MySQL compatibility, pipeline reliability, transformation capabilities, scalability, pricing transparency, and operational overhead.We also reviewed G2 and Capterra ratings and real-world customer feedback to provide a balanced assessment of each platform.

Whether you're replacing custom scripts, replicating MySQL data to a cloud warehouse like Snowflake or Redshift, or synchronizing data from sources such as PostgreSQL, MongoDB, or HubSpot into MySQL, this post will help you compare the leading MySQL ETL tools and choose the one that best fits your architecture and budget.

Top 12 ETL Tools for MySQL

CategoryToolBest ForKey StrengthsLimitationsStarting Price
No-code / managed ELTHevo DataNo-code with real-time CDC, built for reliabilityAuto-healing CDC, transparent pricing, native Databricks Partner Connect integrationCloud-onlyFree plan available; paid plans start at $239/month
No-code / managed ELTFivetranManaged ELT at scale500+ connectors, auto schema evolution, CDCLimited customizationFree tier; paid from $120/mo
Low-code / Visual ETLIntegrate.ioSMB ETL automationVisual pipelines, ETL/ELT, reverse ETLExpensive, limited custom connectorsFrom $15K/year
Low-code / Visual ETLDomoTeams combining MySQL ETL with embedded dashboarding1,000+ connectors, bi-directional data flows, built-in visualizationWorkflow customization is limitedCustom
Low-code / Visual ETLMatillionCloud warehouse ELTPush-down transformations, native MySQL supportLearning curve, usage-based pricingFrom ~$2/credit
Enterprise ETL/ELTQlik Talend CloudGoverned enterprise data integrationData lineage, governance, 900+ connectorsTechnical setup requiredCustom
Enterprise ETLPentaho PDIAutomated enterprise ETLSpoon UI, JDBC support, error handlingAging platform, limited future supportFree CE; Enterprise custom
Developer-Grade & Open-SourceApache SparkLarge-scale data processingDistributed compute, high performanceCode-intensiveFree (OSS)
No-code / Managed ELTSkyviaSaaS & database sync200+ connectors, reverse ETL, bidirectional syncNo streaming, limited transformationsFree; paid from $99/mo
Developer-Grade & Open-SourceAirbyteCustomizable ELT pipelines600+ connectors, CDC, self-hostedSelf-hosting overheadFree OSS; Cloud from $10/mo
Developer-Grade & Open-SourcedbtSQL-based data transformationTesting, lineage, documentationTransformations onlyFree Core; Cloud from $100/user/mo
No-code / Managed ELTStitchSimple managed data replicationManaged connectors, automatic schema detectionLimited transformationsFrom $100/mo
Your MySQL Pipeline Works. Until Someone Alters a Table.
Hevo handles real-time CDC, automatic schema changes, reliable retries, and multi-destination loading without the fragility of traditional MySQL pipelines.
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Top 12 Best MySQL ETL Tools in 2026

Overview G2 4.4/5 (292)

Hevo Data is a cloud-based, no-code ELT platform built for simple, reliable, and transparent data movement. It supports MySQL BinLog-based CDC, monitors binary logs directly, and automatically handles schema changes and source issues to keep pipelines running. Hevo also supports CDC across PostgreSQL, SQL Server, MongoDB, and Oracle, providing a unified data movement layer with minimal engineering effort and full pipeline visibility.

Key Features
Real-time data replication: Hevo captures incremental inserts, updates, and deletes from MySQL binary logs using log-based CDC, keeping destination data synchronized without polling.
Auto-healing pipelines: Automatic retries and recovery help pipelines continue running when source systems experience failures or schema changes.
No-code setup: Teams can configure MySQL as a source or destination through a visual interface without scripting or infrastructure management.
Multi-database CDC: Hevo supports CDC across MySQL, PostgreSQL, SQL Server, MongoDB, and Oracle through database-specific replication methods.
Pipeline visibility: Monitoring and alerts provide visibility into ingestion status, load progress, data usage, and pipeline health.
Pros & Cons
Pros
  • No-code interface makes pipeline setup simple for non-technical users.
  • Automatic schema handling and retries reduce pipeline maintenance.
  • Built-in transformations help prepare data for analytics.
  • Supports multiple databases and destinations through a unified platform.
  • Real-time monitoring and alerts provide clear pipeline visibility.
Cons
  • Cloud-only deployment may not suit teams requiring fully self-hosted pipelines.
  • Usage-based pricing can become expensive as event volumes grow.
  • Complex transformations may require additional technical expertise.
Pricing
PlanPriceEvents/MonthKey Features
Free$0Up to 1M eventsFree sources, 1-hour scheduling, up to 5 users
StarterFrom $239/month annuallyUp to 5M events150+ connectors, dbt integration, SSH/SSL, live chat support
ProfessionalFrom $679/month annuallyUp to 20M eventsUnlimited users, Hevo APIs, streaming pipelines
Business CriticalCustomCustomRBAC, SSO, VPC peering, multiple workspaces, advanced security
Customer Review

Experienced a powerful automated pipeline that offers flexible object selection, effectively cutting costs. Enjoy a user-friendly interface paired with quick and reliable support to enhance productivity. Integrations are simple, and it is easy to identify the required objects and pipeline. I can monitor performance without lag.

Nikhil K., Business Analyst, Mid-Market (51-1000 emp.) G2 review
How Scale Media Saved 60 Hours Every Month With Hevo
Scale Media replaced manual MySQL API connectors with automated pipelines to Redshift, saving 60 hours monthly while achieving zero failures and 100% data accuracy.
Read the Case Study
Overview G2 4.3/5 (829)

Fivetran is a fully managed ELT platform for teams that need a hands-off way to move data into MySQL. It supports 500+ sources and automates pipeline maintenance, schema updates, CDC, and incremental data loading. Fivetran is well suited to enterprise teams with complex data stacks and limited engineering resources.

Key Features
Automatic schema management: Fivetran detects source schema changes, including new or renamed columns, and applies supported changes automatically.
Hands-free maintenance: Fivetran monitors pipelines, handles incremental syncs, and retries failures automatically to reduce manual maintenance.
Native MySQL integration: Connect data from CRMs, ERPs, marketing platforms, databases, and other sources to MySQL through managed connectors.
CDC and incremental loading: Change data capture and incremental syncs keep MySQL data fresh while reducing unnecessary source-system load.
Pros & Cons
Pros
  • Fully managed ELT pipelines require minimal setup and ongoing maintenance.
  • Automated schema management reduces manual pipeline updates when source structures change.
  • CDC and incremental loading provide reliable, efficient data synchronization.
  • Broad connector coverage supports complex enterprise data stacks.
Cons
  • Custom connectors require additional development and maintenance.
  • Limited customization compared with code-first ETL platforms.
  • Consumption-based pricing can become expensive as data volume increases.
  • Does not provide reverse ETL capabilities.
Pricing
PlanEvents/MonthNotes
FreeUp to 500K MARLimited connectors
StandardMAR-based~$12K/year minimum; 1-hour sync
EnterpriseMAR-basedEnterprise DB connectors, SLA support
Business CriticalMAR-basedPrivate links, custom encryption keys
Customer Review

Fivetran is extremely simplistic, with manageable configurations that take no time. But it can be an expensive product, more so when data volume keeps increasing.

Luciana S., IT Manager, Health, Wellness and Fitness G2 review
Overview G2 4.3/5 (213)

Integrate.io is a low-code data integration platform for small to mid-sized businesses that need to move data to and from MySQL without extensive engineering effort. It supports ETL, ELT, reverse ETL, and CDC through 200+ connectors. Its visual interface helps teams clean, map, join, and transform data while scheduled workflows automate data movement with minimal maintenance.

Key Features
Pre-built MySQL connector: Integrate.io supports data extraction and loading for MySQL with batching and retry logic for reliable data movement.
Visual data transformation: Clean, map, join, and transform data through a drag-and-drop interface without relying on custom SQL or scripts.
Scheduled and automated workflows: Run ETL jobs on schedules or event triggers and keep MySQL data updated with minimal manual intervention.
CDC and reverse ETL: Supports change data capture and reverse ETL alongside traditional ETL and ELT workflows.
Pros & Cons
Pros
  • Supports ETL, ELT, reverse ETL, and CDC in one platform.
  • Visual low-code interface simplifies data transformation and pipeline development.
  • Fixed monthly pricing provides predictable costs without consumption-based billing.
  • Dedicated Solution Engineer and responsive customer support help with onboarding and troubleshooting.
Cons
  • Incomplete documentation can make custom transformations and connectors harder to implement.
  • Detailed error logs and troubleshooting information can be limited.
  • Limited API support for some integrations beyond the REST API.
  • Higher starting price may not suit teams with simple or low-volume ETL needs.
Pricing
PlanPriceData VolumeKey Features
Standard$1,999/monthUnlimited200+ connectors, CDC, reverse ETL, 60-sec replication, dedicated Solution Engineer
EnterpriseCustomUnlimitedAdvanced security, SLA guarantees, custom connectors
Customer Review

It’s easy to create ETL transformations, and the customer service and support team responds quickly.

Ajanthan M., Data Analyst G2 review
Overview G2 4.3/5 (700)

Domo is a cloud-based data integration, business intelligence, and analytics platform that combines MySQL data integration with dashboards and visualization. Its ETL and SQL dataflow capabilities let teams connect, transform, and analyze data in one platform. With 1,000+ pre-built connectors, Domo is well suited to enterprise teams that want data pipelines and analytics without managing separate tools.

Key Features
MySQL connector: Domo connects to on-premises and cloud-hosted MySQL databases to import data for transformation, analysis, and visualization.
ETL and SQL dataflows: Teams can build data pipelines and apply SQL-based transformations directly within Domo.
1,000+ connectors: Pre-built connectors support data ingestion from databases, SaaS applications, cloud services, and other business systems.
Integrated dashboards and analytics: Domo combines data integration, interactive dashboards, reporting, and analytics in a single platform.
Data collaboration: Real-time data access and collaboration features help business teams work with shared datasets and insights.
Pros & Cons
Pros
  • Combines ETL, dashboards, analytics, and data visualization in one platform.
  • Offers 1,000+ pre-built connectors for broad data integration.
  • User-friendly dashboards simplify data exploration and reporting.
  • Supports real-time data accessibility and collaboration.
Cons
  • Complex dashboards and advanced workflows may require technical expertise.
  • Workflow customization can be limited for highly specialized requirements.
  • Performance can become challenging when processing very large datasets.
  • Consumption-based pricing can make costs harder to predict at scale.
Pricing
PlanPriceKey Features
Free Trial$0 (30 days)Full platform access, unlimited users, no credit card required
PaidCustomConsumption-based credits covering data ingestion, ETL, dashboards, and AI queries
Customer Review

It is very useful for data analysis and automation; it is easy to load the information and the design is very user-friendly.

Adolfo M., Risk Manager, Airlines/Aviation G2 review
Overview G2 4.5/5 (125)

Matillion is a cloud-native ETL/ELT platform for analytics engineering teams that need warehouse-native data integration and transformation. It supports MySQL connectivity and integrates with platforms such as Snowflake, Amazon Redshift, Google BigQuery, and Databricks. Its visual job designer, advanced orchestration, and transformation capabilities make it well suited to mid-size and large teams building scalable data pipelines.

Key Features
Native MySQL connectivity: Extract and load data from MySQL using Matillion's native connectivity and integrate it into cloud data warehouse workflows.
Incremental data loading: Move only new or updated records to reduce pipeline runtime and improve data transfer efficiency.
Warehouse-native transformations: Use ELT to transform data directly within the destination warehouse for scalable processing and performance.
Visual job designer: Build and orchestrate data pipelines through a visual interface with reusable components and workflow controls.
Advanced orchestration: Manage complex pipelines with scheduling, dependencies, APIs, and automation across cloud data platforms.
Pros & Cons
Pros
  • Pushes transformations into the warehouse for scalable ELT processing.
  • Strong visual interface for designing and managing complex data workflows.
  • Supports Python and SQL alongside visual pipeline development.
  • Integrates closely with Snowflake, Redshift, BigQuery, and Databricks.
  • Advanced orchestration and governance features support enterprise data teams.
Cons
  • Steep learning curve can make adoption challenging for new users.
  • Credit-based pricing can become expensive as data usage and environments increase.
  • Performance depends heavily on the capabilities of the destination warehouse.
  • Some users report occasional web UI and pipeline development issues.
Pricing
PlanPriceKey Features
DeveloperFreeLimited features, single user
TeamsCustom (credit-based)Visual job designer, 150+ connectors, warehouse-native ELT
ScaleCustom (credit-based)Advanced orchestration, Maia AI assistant, enterprise governance
Customer Review

Maia’s AI features save me a lot of time when planning and developing data pipelines. The problem it shows is that the web UI can occasionally get buggy, and I sometimes have to refresh the page just to link components.

Malachi N., Data Engineer G2 review
Overview G2 4.6/5 (100)

Qlik Talend Cloud is an enterprise data integration platform for organizations managing complex, multi-source data environments. It combines ETL, ELT, data quality, governance, and CDC capabilities with hybrid and multi-cloud deployment options. Its broad connector ecosystem and centralized governance features make it well suited to large enterprises that need scalable and governed MySQL data integration.

Key Features
900+ connectors: Connect MySQL with SaaS applications, databases, legacy systems, cloud platforms, and other enterprise data sources through a broad library of pre-built connectors.
Change data capture: Capture and replicate changes from supported databases to keep downstream systems synchronized with current data.
Data quality and governance: Profile, validate, monitor, and govern data while maintaining visibility across enterprise data environments.
ETL and ELT transformations: Build data pipelines with transformation capabilities for preparing and moving MySQL data across different destinations.
Hybrid and multi-cloud deployment: Support complex enterprise environments with flexible deployment options across cloud and on-premises infrastructure.
Pros & Cons
Pros
  • Combines data integration, quality, governance, and CDC in one platform.
  • Broad connector coverage supports complex multi-source environments.
  • Hybrid and multi-cloud deployment options provide enterprise flexibility.
  • Strong governance capabilities support regulated and governance-heavy organizations.
  • Visual pipeline development simplifies connector setup and data transformation.
Cons
  • Advanced configurations can require significant technical expertise.
  • Pricing is primarily custom and can be difficult for smaller teams to evaluate.
  • The broad feature set can create a steeper learning curve for new users.
  • The user interface may feel less intuitive for some users.
Pricing
EditionPriceKey Features
StarterCustomSaaS application replication, limited database sources, managed gateway
StandardCustom; from ~$3,300/monthCDC support, unlimited databases, private network access, 15-min scheduling
PremiumCustomAdvanced ETL/ELT transformations, data quality, API integration, governance
EnterpriseCustomMaster data management, highest capacity, full governance suite
Customer Review

With the platform's simplicity, it is effortless to set up a source connector, transform the data using a simple SQL editor and send it wherever I want. The UI is a little unpleasant to the human eye, but it is a small thing compared to the system's functionality and simplicity.

Ido A., Head Of Data And BI G2 review
Overview G2 4.1/5 (59)

Pentaho Data Integration (PDI), also known as Kettle, is a visual, Java-based ETL platform for designing, orchestrating, and automating data pipelines. It provides strong MySQL connectivity through JDBC and supports batch and real-time data integration. PDI is well suited to data engineering teams running on-premise infrastructure that need robust ETL capabilities without requiring a cloud-native deployment.

Key Features
MySQL connectivity: PDI provides out-of-the-box MySQL connectivity through JDBC drivers for stable and secure data integration workflows.
Visual ETL designer: Build transformations and jobs through a graphical interface without writing extensive custom code.
Batch and real-time integration: Support batch processing and real-time data integration for different MySQL pipeline requirements.
Error handling and monitoring: Built-in logging, error handling, and monitoring capabilities help teams identify and manage pipeline issues.
ETL orchestration: Automate complex data workflows with scheduled jobs, reusable transformations, and workflow dependencies.
Pros & Cons
Pros
  • Strong MySQL connectivity through JDBC and visual pipeline development.
  • Supports both batch and real-time data integration workflows.
  • Built-in error handling, monitoring, and logging simplify pipeline management.
  • Community Edition provides core ETL capabilities at no cost.
  • Well suited to on-premise environments and large-scale data processing.
Cons
  • Cloud-native deployment capabilities are more limited than newer SaaS ETL platforms.
  • Complex jobs can be time-consuming to modify and maintain.
  • Documentation and troubleshooting resources can be limited.
  • Advanced enterprise features require a commercial license.
Pricing
EditionPriceKey Features
Community EditionFreeCore ETL features, visual designer, MySQL connector, no official support
Enterprise EditionCustomETL clustering, high availability, metadata-driven lineage, official support
Customer Review

Pentaho Business Analytics is a very advanced, hardware-compatible ETL system which can handle large amounts of data rapidly. It would be nice to have a replication template on objects, tables, bridge-tabs, maps, which would help the layout. I think many core elements must be improved.

Andreas W., Information Technology Consultant G2 review
Overview G2 4.1/5 (54)

Apache Spark is a distributed data processing engine that integrates with MySQL for large-scale ETL, analytics, and data engineering workflows. It connects to MySQL through JDBC and can process data across distributed clusters using Python, Java, Scala, and SQL. Spark is best suited to teams processing large MySQL datasets as part of broader data lake and distributed data architectures.

Key Features
MySQL connectivity: Spark connects to MySQL through JDBC, allowing Spark jobs to read from and write to MySQL tables.
Distributed processing: Process large MySQL datasets across distributed clusters instead of relying on a single database server.
Multi-language support: Build data pipelines and analytics workflows using Python, Java, Scala, or SQL.
Large-scale ETL: Transform and process high-volume MySQL data as part of data lake and enterprise data engineering workflows.
Advanced analytics: Support SQL analytics, machine learning, and batch or streaming workloads within the same distributed processing framework.
Pros & Cons
Pros
  • Handles large-scale data processing across distributed computing clusters.
  • Supports Python, Java, Scala, and SQL for flexible development.
  • Can process MySQL data alongside multiple sources and destinations.
  • Supports complex ETL, analytics, and data engineering workloads.
  • Open-source distribution provides flexibility without software licensing costs.
Cons
  • Requires technical expertise to design, deploy, and maintain distributed Spark workloads.
  • Self-managed deployments require additional infrastructure and operational resources.
  • Failed distributed jobs can require significant troubleshooting and reruns.
  • May be excessive for simple MySQL ETL workloads with modest data volumes.
Pricing
DeploymentPriceNotes
Open SourceFreeSelf-managed; infrastructure costs vary
AWS EMR / DatabricksPay-per-useManaged Spark; compute and storage billed separately
Customer Review

Spark's fast computing allows for a more interactive experience. It also allows the extensive exploration of data using SQL, Python or Scala. I wish there were a way to process large amounts of data without having to restart from scratch once it crashes.

Amrita C., Business Analyst, Information Technology and Services G2 review
Overview G2 4.8/5 (135)

Skyvia is a no-code cloud data integration platform that connects MySQL with 200+ SaaS applications, databases, and data warehouses. Built by Devart, it combines ETL, ELT, replication, and backup capabilities in one platform. Skyvia supports MySQL as both a source and destination, making it suitable for small to mid-sized businesses that need flexible data integration without extensive engineering effort.

Key Features
Import and export: Build one-way data transfers between MySQL and 200+ connectors, including CRM, ERP, database, and data warehouse systems.
MySQL replication: Keep MySQL synchronized with supported cloud sources on scheduled intervals, with higher tiers supporting frequent synchronization.
Data Flow designer: Build multi-source pipelines with visual mapping, filtering, and deduplication for more complex integration scenarios.
No-code integration: Configure data pipelines and synchronization workflows through a visual interface without writing custom integration code.
Data backup: Back up MySQL and other supported data sources to help protect business data and support recovery workflows.
Pros & Cons
Pros
  • No-code interface is accessible to non-technical users and business teams.
  • Free tier allows teams to test basic integrations before upgrading.
  • Broad connector library covers SaaS applications, databases, and warehouses.
  • Supports ETL, ELT, replication, and backup within one platform.
  • MySQL can be configured as either a source or destination.
Cons
  • Scheduling is not true real-time CDC and can reach once-per-minute intervals only on higher tiers.
  • Separate pricing for different modules can make cost forecasting more complicated.
  • Complex joins and aggregations are more limited than in dedicated ETL platforms.
  • Advanced integration scenarios may require higher-tier plans.
Pricing
EditionPriceKey Features
FreeFree10k records per month, basic integration scenarios, basic integration for small volumes of data
Basic$79/mo.Basic data ingestion and ELT scenarios, simple mapping features
Standard$159/mo.ELT and ETL scenarios, 50 scheduled integrations, advanced mapping features
Professional$399/mo.Powerful data pipelines for any scenario
Customer Review

Honestly the biggest win for me is how easy it is to get up and running. I’m not a developer and I don’t have time to learn complicated scripting just to move data between our ERP and a few cloud apps we use for supplier tracking. With Skyvia, I set up my first sync in about twenty minutes.

Emily C., Procurement Specialist G2 review
Overview G2 4.4/5 (221)

Airbyte is an open-source ELT platform with 600+ connectors, including MySQL as both a source and destination. It uses log-based CDC to read MySQL binary logs and replicate changes with minimal load on the source database. Teams can self-host Airbyte for greater infrastructure control or use Airbyte Cloud for a managed experience, making it a flexible option for engineering-driven organizations.

Key Features
Log-based CDC: Reads MySQL binary logs asynchronously to capture inserts, updates, and deletes with minimal impact on the source database.
600+ connectors: Connect MySQL with a broad range of databases, SaaS applications, APIs, and other data sources and destinations.
Connector Development Kit: Build custom connectors for internal or niche data sources that are not available in the pre-built connector catalog.
Flexible deployment: Self-host Airbyte on your own infrastructure or use Airbyte Cloud for a managed data integration experience.
Incremental data synchronization: Replicate only new or changed records to reduce unnecessary data movement and improve pipeline efficiency.
Pros & Cons
Pros
  • Large connector catalog provides broad integration coverage.
  • Self-hosted deployment offers full control over infrastructure and data.
  • Open-source architecture reduces vendor lock-in and software licensing costs.
  • CDC supports near real-time replication from MySQL.
  • Extensible framework allows teams to develop custom connectors.
Cons
  • Self-hosting requires DevOps resources for infrastructure, monitoring, upgrades, and incident response.
  • No built-in transformation layer means teams often need a separate tool such as dbt.
  • Cloud pricing is credit-based and can increase with higher data volumes.
  • Cloud sync frequency depends on the selected plan and may not suit true real-time requirements.
Pricing
PlanStarting PriceKey Inclusions
Open Source (Self-hosted)FreeAll connectors, full infrastructure control, community support
Individual$29/monthAPI and MCP access, Standard and AI support, overage AOs priced at $0.004
Teams$299/monthMultiple users and workspaces, Standard and AI support, overage AOs priced at $0.005
EnterpriseCustomSelf-hosted with enterprise support, SLAs, audit logs
Customer Review

Open-Source & Flexibility: Airbyte OSS stands out for its open-source approach. It's both free and self-hostable, providing full control over data and infrastructure while eliminating vendor lock-in.

Hardik S., Marketing Expert G2 review
Overview G2 4.7/5 (199)

dbt (data build tool) is a SQL-based transformation platform that teams pair with extraction and loading tools such as Hevo, Airbyte, or Stitch. Rather than extracting or loading MySQL data, dbt transforms data after it has landed in a supported warehouse or data platform. It brings version control, automated testing, documentation, and CI/CD practices to analytics workflows, making it well suited to analytics engineering teams.

Key Features
Version-controlled SQL models: Define modular SQL transformations and manage them in Git alongside tests, documentation, and configuration.
Automated data testing: Validate assumptions such as uniqueness, non-null values, and referential integrity before transformed data reaches downstream analytics.
Lineage and documentation: Automatically generate dependency graphs and documentation showing how models relate to source tables and downstream assets.
Warehouse-native transformations: Execute SQL transformations directly within supported cloud data warehouses and platforms using their existing compute resources.
CI/CD workflows: Integrate data transformations into software development workflows with version control, automated testing, code review, and deployment processes.
Pros & Cons
Pros
  • Industry-standard transformation tool with a large community and extensive learning resources.
  • Brings version control, testing, CI/CD, and code review practices to SQL workflows.
  • dbt Core is free and open-source for teams managing their own infrastructure.
  • Strong lineage and documentation capabilities improve data discoverability and governance.
  • Modular SQL models make complex transformation workflows easier to maintain.
Cons
  • Only handles data transformation and requires a separate tool to extract and load MySQL data.
  • Primarily designed for major cloud data warehouses rather than MySQL directly.
  • dbt Cloud costs increase with developer seats and job usage.
  • Warehouse compute costs are separate from dbt Cloud subscription costs.
  • Teams new to analytics engineering may face a learning curve around SQL modeling and project structure.
Pricing
PlanStarting PriceKey Inclusions
DeveloperFreeBrowser-based IDE, multi-factor authentication (MFA), job scheduling
Starter$100 per user/monthdbt Catalog basic, dbt Semantic Layer basic, dbt Copilot code generation, API access
EnterpriseCustomdbt Copilot, dbt Canvas, dbt Insights, dbt Catalog advanced
Enterprise+CustomPrivateLink, IP restrictions, rollback, hybrid projects
Customer Review

The way it handles large amounts of data, as well as how it integrates into AWS (S3/Glue) is great. This allows me to avoid building custom pipelines which would have been very time consuming.

Joseph S., Software Developer G2 review
Overview G2 4.8/5 (68)

Stitch is a cloud-based ELT platform, now part of Qlik Talend Cloud, designed to replicate data from SaaS applications and databases into cloud data warehouses with minimal setup. Built on the open-source Singer framework, Stitch provides managed connectors, automatic schema detection, scheduling, and monitoring. It is well suited to small and mid-sized data teams that need straightforward extraction and loading without extensive engineering effort.

Key Features
Singer-based connectors: Provides 130+ managed connectors and supports custom Singer taps for sources not covered by the standard connector library.
Automatic schema detection: Detects supported MySQL schema changes and adjusts destination tables without requiring manual pipeline updates.
Replication scheduling: Configure synchronization schedules and retain extraction logs to monitor and troubleshoot pipeline runs.
Managed data replication: Automates extraction and loading from MySQL and SaaS applications into supported cloud data warehouse destinations.
MySQL integration: Connect MySQL databases as data sources and replicate their data to cloud destinations with minimal configuration.
Pros & Cons
Pros
  • Fast and straightforward setup is suitable for teams building their first data stack.
  • Managed connectors reduce infrastructure and pipeline maintenance requirements.
  • Automatic schema detection simplifies handling of source database changes.
  • Singer framework enables custom connectors for unsupported sources.
  • 14-day free trial provides an opportunity to test the platform before committing.
Cons
  • No built-in transformation layer, so teams need dbt or another tool for data transformations.
  • Row-based pricing can make costs increase as data volume grows.
  • Connector and destination options are more limited than larger ELT platforms.
  • Changes in ownership may create uncertainty around long-term product direction.
Pricing
PlanPriceRows/MonthDestinationsSourcesUsers
Standard$100/mo5M–300M (configurable)110 standard5
Advanced$1,500/mo (annual)100M3Unlimited (incl. enterprise)Unlimited
Premium$3,000/mo (annual)1B5Unlimited (incl. enterprise)Unlimited
Customer Review

I appreciate how Stitch has been helping us migrate and onboard with Braze as our marketing automation platform, rapidly aiding our technical teams to get past the learning curve. Their solutions are really well thought out and documented.

Randall R. G2 review

How to Choose an ETL Tool for MySQL Database?

Evaluate MySQL ETL tools based on the factors that directly affect pipeline flexibility, reliability, speed, and the quality of data delivered to your destination.

01

Data Source Integration

Look for comprehensive connector support across databases, SaaS applications, marketing platforms, and other systems to future-proof your MySQL pipelines.

02

Monitoring & Management

Prioritize tools with monitoring, error handling, alerts, and clear workflow controls to identify issues and keep pipelines running reliably.

03

Real-Time Data Streaming

Choose real-time or CDC capabilities when your workflows require fresh MySQL data instead of relying only on scheduled batch processing.

04

Reliable Data Loading

Evaluate loading accuracy, destination compatibility, failure recovery, and warehouse integration to prevent inefficient pipelines and unreliable data delivery.

Conclusion

You have now seen various free tools for MySQL. While most of them provide an open-source edition, it may be beneficial to subscribe to the paid edition for added benefits. This article seeks to familiarize you with the different available tools to enable you to make the right choice.

Hevo is a cloud-based, no-code ETL platform built with the focus of data ingestion and ETL services. It offers a full-scale database replication system that is incremental and integrated with additional features such as timestamp and changing the data capture system.

Sign up for a 14-day free trial now.

FAQ

What is MySQL data integration?

MySQL data integration is the process of combining data from one or more MySQL databases or integrating MySQL with other data sources to build a unified system. This helps improve reporting, analysis, and decision-making across a centralized data environment.

What is an ETL in SQL?

ETL in SQL involves extracting data from various sources, transforming it to fit operational needs, and loading it into a target database.

Is MySQL a data warehouse tool?

No, MySQL is not a data warehouse tool; it is a relational database management system (RDBMS) designed primarily for transactional processing rather than complex data warehousing.

What are the benefits of MySQL ETL tools?

There are several advantages to MySQL ETL tools, such as simplifying complex data workflows by automating them, reducing the need for custom code, and enabling teams to move faster without technical overhead. They also help automate data workflows for faster migration and transfer.

Are open-source ETL tools suitable for large MySQL databases?

Open-source tools like Apache Spark or Talend Open Studio can handle large datasets, but some lightweight tools like Apatar or Csv2db may struggle with high volumes or complex transformations.

How do I choose the right MySQL ETL tool?

Consider factors such as real-time data support, integration with multiple sources, ease of setup, monitoring capabilities, scalability, and data transformation features.

What are the benefits of using a no-code ETL platform for MySQL?

No-code platforms simplify setup, provide real-time integration, reduce maintenance, support multiple data sources, and make ETL accessible to non-technical users.

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