Airbyte vs Meltano – What’s Best for Your ELT Needs? 

It’s not easy to pick the winner in the Airbyte vs Meltano comparison. Both tools are open-source and can be self-hosted. But they cater to different users and data integration use cases.

Airbyte focuses on accessibility with 600+ production-ready data connectors. On the other hand, Meltano’s code-first configuration approach attracts data engineers who want complete control over their data pipelines. 

To write this detailed Meltano vs Airbyte comparison article, we’ve conducted extensive research and testing so that you can pick the right ELT (Extract, Load, Transform) solution for your data pipeline. 

What is Airbyte?

Airbyte is an open-source ELT platform available in both cloud and self-hosted deployments. You can use it to sync your data from databases, SaaS apps, and APIs to warehouses and data lakes.

Thanks to its low-code interface, non-developer users can get started quickly. The open-source foundation enables data engineers to build, customize, or self-host their pipelines with minimal friction. 

The ease of use is largely driven by Airbyte’s extensive connector ecosystem. It currently offers a growing library of over 600 connectors. As a result, you can start syncing data from a wide range of sources in minutes.

What’s more, you can contribute to, extend, and modify connectors, indicating that the platform supports a community-driven architecture.

We’ve tried Airbyte to gather hands-on information for this article and found it easy to set up, especially with the AI-powered Connector Setup Assistant. 

Airbyte supports over 20 leading destinations, including Databricks Lakehouse, Postgres, Snowflake, Firebolt, Salesforce, and more. 

• It currently has a 4.4 out of 5 rating based on 75 reviews on G2. 

What is Meltano?

Like Airbyte, Meltano is an open-source data integration tool. 

As Meltano takes the CLI-first approach, it’s best for data engineers and developers who prioritize control, transparency, and customization in their data pipelines. 

For testing purposes, we’ve installed Meltano in a Docker container. 

It’s built on the Singer standard, so you can extract data from any source (tap) and load it to any target. 

Moreover, Meltano’s modular, CLI-first approach facilitates integration with existing DevOps workflows and supports CI/CD and Git-based version control. 

The plugin-based architecture enables a cohesive data stack by allowing users to incorporate various tools, including the data build tool (dbt), for transformations.

• Meltano presently has a 4.9 out of 5 rating based on seven reviews on G2.

Airbyte vs Meltano vs Hevo – A Quick Eye View

Use Cases & Architecture Fit

Airbyte	Meltano	Hevo
Primarily ELT with batch and real-time ingestion	Full ELT lifecycle with integrated dbt transformations	No-code ELT platform focused on operational analytics
Modular and flexible architecture for customization	Extensible through plugins for diverse needs	Designed for ease of use with minimal technical overhead

Connectors & Data Sources

600+ connectors, including CDC support	Supports various data sources with plugin-based extensions	150+ pre-built connectors with automatic schema management
Community-driven development enables rapid connector growth	Community-driven and decentralized ecosystem	Supports batch and real-time ingestion

Total Cost of Ownership

Free open-source version available	Fully open source with no licensing fees	Paid fully managed service with tiered pricing
Cloud and enterprise versions are priced by volume and capacity	Self-hosted only; managed hosting available via Matatika Cloud (acquired Meltano in December 2025)	Cost scales based on data volume processed

Implementation & Deployment Complexity

Requires technical setup and maintenance	Setup requires engineering resources	Quick, no-code deployment with minimal setup
Highly customizable for complex workflows	Plugin management adds configuration complexity	Designed for users with limited technical expertise

Performance & Scalability

Handles large datasets with incremental syncing	Performance depends on plugin configurations	Optimized for high performance and scalability
Supports scalable architecture for growing data needs	May require tuning for very large data volumes	Efficiently manages large data volumes in real-time

Maintenance & Operations

Requires ongoing maintenance and updates	Maintenance of plugins needed	Minimal maintenance due to fully managed support
Active community support and frequent updates	Community-driven support	Dedicated customer support and service

Airbyte vs Meltano – In-depth Features Comparison

Here is a detailed feature comparison of Airbyte and Meltano based on our testing and research.

Pre-built Connectors 

Airbyte 

It provides more than 600 pre-built connectors, with a strong focus on SaaS APIs. The open-source connector framework and community focus allow you to develop connectors tailored to your specific use cases using a no-code CDK.

Meltano 

Meltano relies on the Singer standard to offer access to over 500 connectors across a community-driven ecosystem, including 300+ Singer taps, plus 200+ Airbyte connectors through a wrapper. 

These connectors are open-source and modifiable, but they are considered complex and require frequent maintenance. 

What’s more, Meltano offers a software development kit (SDK) and an extractor development kit (EDK) to help you create or extend high-quality Python connectors.

Result 

Teams prioritizing rapid deployment and broad out-of-the-box integrations may lean toward Airbyte, while developer-centric teams seeking deep customization and control may prefer Meltano.

User Interface + Developer Workflow

Airbyte 

Airbyte has an intuitive user interface that caters to users of varying skill levels. The low-code UI makes it easy for non-engineers to build visual pipelines. 

The visual representation of data pipelines and drag-and-drop functionality make defining and managing pipelines straightforward. 

Airbyte also supports a REST API for code-based automation, but workflow integration may require custom scripts.

Meltano 

Meltano prioritizes a developer-first user experience, which may make it difficult for non-technical users to use the tool effectively. 

It takes a CLI-first approach, treating pipelines as code and supporting native Git version control, CI/CD integration, and environment management. 

However, the solution lacks a full-featured visual interface.

Result

There is no clear-cut winner in this category. Airbyte is the first choice for ease of use, and Meltano shines when you want complete control over your data pipelines. 

Transformations

Airbyte 

In Airbyte, transformations occur after loading, using SQL and dbt, to produce structured data at the destination. 

Airbyte Cloud includes a dbt Cloud integration that automatically triggers dbt Cloud jobs immediately after each sync completes. This works for teams that wish to apply business logic after ingestion. 

Airbyte supports post-loading transformation, but doesn’t support in-line or pre-load transformation logic.

Meltano

Meltano gives developers complete control over post-load transformations by integrating dbt as the core of its pipeline. It also supports pre-load changes through mappers that filter fields or rename columns before loading. 

The dual pre- and post-load approach allows more control and flexibility for structured pipelines. The CI/CD workflows are best for teams that treat transformations as code.

Result 

For teams that require both pre- and post-load transformations, Meltano is the top choice. Businesses that need an easy-to-start ELT tool will find Airbyte a better option. 

Customizability

Airbyte 

With Airbyte’s Connector Development Kit, customization is quick and easy. Teams can build and adapt bespoke connectors within hours. The tool supports modular integration with orchestrators like Airflow. 

Airbyte also accepts contributions to its codebase, and self-hosting offers much greater flexibility for engineering teams.

Meltano 

Since Meltano relies on the tap-and-target model, it offers developers full control to customize or build new connectors using the SDK. The modular plugin architecture enables teams to customize each pipeline stage using their preferred tools. 

Users can code their own Singer tap to connect to any long-tail source, but teams remain responsible for development and maintenance.

Result 

When pre-built connectors don’t support proprietary systems or legacy databases, customizability determines whether you can extend the platform or hit a dead end.

Meltano scores higher in this category, offering the flexibility to build connectors for virtually any source.

While Airbyte’s CDK enables rapid connector development, it lacks the granular, stage-by-stage customization of Meltano’s modular plugin architecture.

Deployment Flexibility 

Airbyte 

Airbyte has two main deployment options: Airbyte Cloud and Self-hosted. For teams that must adhere to strict security or compliance requirements, self-hosting Airbyte on their own infrastructure is a sensible option. 

Other teams can opt for an end-to-end managed cloud solution to avoid the overhead of setup and maintenance. The dual approach makes Airbyte a suitable data pipeline solution for both early-stage startups and enterprise data teams.

Meltano 

Conversely, Meltano is designed specifically for self-hosting. It’s an ideal tool for teams that want deep DevOps integration and data ownership. The tool offers full visibility over the environment, infrastructure, and pipeline configuration. 

While Meltano itself doesn’t offer a native cloud service, managed hosting options exist. 

The original Meltano Cloud was rebranded to Arch in late 2023, and in December 2025, Matatika acquired Meltano and now offers Matatika Cloud as a managed option. 

However, these are third-party services rather than a first-party Meltano offering. So teams choosing Meltano should plan for self-hosting or evaluate these alternatives separately.

Because Meltano’s managed options are third-party rather than native, you should factor in the additional evaluation effort and potential integration differences when choosing this path.

Result 

Airbyte wins on deployment flexibility with its native dual-deployment model, offering self-hosted and first-party-managed options. It is suitable for teams with diverse skill sets.

Meltano, while strong for self-hosting scenarios, relies on third-party services for managed hosting, adding complexity to the evaluation and implementation process.

Maintenance and support

Airbyte 

Airbyte outperforms Meltano in the maintenance and support segment. You have multiple support options, including detailed documentation, a status page that displays your real-time and historical performance, a GitHub community, and a Slack community. 

Fixed-hours agent support is also available for Airbyte Cloud and Enterprise customers.

Meltano 

Turning to Meltano, its support model differs significantly from Airbyte’s. It offers free community support in Slack. 

Users can also purchase custom support packages, which include implementation of services and connectors, priority support with SLA, training, and more.

Result 

You’ll need support when your data pipelines break, and Airbyte is a clear top choice with its diverse support options. Meltano only offers community-based support, though you can buy a premium customer support package separately. 

Airbyte or Meltano? What’s The Best Option?

Airbyte suits teams that need a modern, low-code interface, flexible deployment, CDC for real-time synchronization, and an active community with frequent product updates. 

It’s a go-to solution for startups and mid-sized businesses looking for ease of use and quick scalability. 

On the other hand, Meltano targets data engineers or DevOps teams seeking self-hosting, CLI workflows, Git integration, version control, customization, and open-source tools like dbt.

As you can see, Airbyte and Meltano both excel in their respective domains. 

However, both share a common challenge: you still need to manage infrastructure. Self-hosted Airbyte and Meltano require DevOps expertise, monitoring setup, and ongoing maintenance.

Airbyte Cloud eliminates infrastructure headaches, yet its volume-based pricing in initial plans may become unpredictable as usage increases.

In fact, one verified reviewer pointed it out on G2,

The data-based pricing model of Airbyte Cloud can feel limiting and not as predictable, especially as data volumes grow. I would prefer a more transparent, resource-based pricing approach that aligns better with infrastructure usage.

Verified Author

View Review

Enter Hevo Data, which offers reliability, transparency, and simplicity in data pipelines without any pricing surprises. 

Why Does Hevo Stand Out

Hevo delivers a 100% managed, truly no-code ELT platform that helps you run data pipelines with minimal effort.

Here’s what makes Hevo different:

• No-code Simplicity – With no script or engineering overhead, you can build, monitor, and debug pipelines with a visual dashboard. 
• Near Real-time Sync – Hevo ensures consistent and real-time data movement with built-in logic, failure alerts, and smart error handling. 
• 24×7 Support – Hevo offers 24/7 customer support and doesn’t rely on community help like other open-source tools. This is why Hevo is consistently rated high for customer support on platforms like G2. 
• Enterprise-Ready Security – SOC 2 Type II compliance, strong access controls, and built-in governance features make Hevo a solid choice for data-sensitive domains.
• In-built Observability – Hevo monitors everything without the need for external tools, such as tracking latency, sync status, getting detailed logs, and more. 
• Auto Schema Handling – Hevo quickly adapts to schema changes, reducing manual interventions and keeping pipelines steady.

Hevo is perfect for fast-scaling businesses or enterprises that want zero-maintenance pipelines, enterprise-grade reliability, and quick time-to-value. 

If you require a seamless data integration that doesn’t require you to code, then Hevo is the right choice for you. 

Reviewing Hevo Data, Henry wrote on G2:

What I like best about Hevo Data is its intuitive user interface, clear documentation, and responsive technical support. The platform is straightforward to navigate, even for users who are new to data migration tools. I found it easy to set up pipelines and manage data flows without needing extensive technical support. Additionally, Hevo provides well-organized documentation that clearly explains different migration approaches, which makes the entire process smooth and efficient.

Henry E.

Software Engineer

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