Top 11 Fivetran Competitors & Alternatives (Free & Paid)

If you are a Fivetran user, you may have struggled with complex configurations, skyrocketing prices, or limited scalability. You are not alone. Several users have reported inadequacies in support, rigid integrations, and a lack of transparency in pricing. These limitations have pushed various users to look for better Fivetran alternatives that provide value for their money.

In this post, we will walk you through why you should consider Fivetran Competitors and present the 11 best options to help you choose the best fit for your data integration needs. 

Our reviews are based on in‑depth research, real user feedback, and firsthand experience, so you can make an informed decision that best suits your business needs.

How Have We Curated This List?
We’ve compiled this list by combining real user reviews on trusted sites like G2 and Capterra with detailed assessments of key features, pricing, scalability, etc.

Our goal was to find solutions that not only address common challenges faced by Fivetran users but also deliver a user-friendly experience without compromising on performance.

What is Fivetran?

Fivetran is a popular cloud-based ELT (Extract, Load, Transform) service that automates the movement of data from various sources into a central data warehouse. It is known for its extensive library of pre-built connectors and its fully managed, zero-maintenance architecture, which simplifies the data ingestion process for many businesses.

The platform aims to make data accessible for analytics without requiring extensive engineering resources for pipeline development and maintenance. Fivetran extracts data from applications, databases, and files, loads it into a destination, and then allows transformations to be run post-load using tools like dbt Core.

When would Fivetran be the right choice for you?

Fivetran is the go-to for companies that want automation and speed instead of building pipelines from scratch. It works best when your business needs match what it does really well. Let’s dive in and take a closer look.

1. When your data stack is growing fast

• As your company expands and new SaaS apps are added, manual integration can quickly become a bottleneck. Fivetran solves this by offering a large set of pre-built connectors for databases, SaaS platforms, and event streams, which makes adding new sources as simple as plugging them in. So what would usually take weeks of engineering effort can be reduced to just a few minutes of setup.

2. When data freshness is critical

• The faster your business moves, the more important it is to work with the latest data. This is especially true in spaces like e-commerce or fintech, where decisions based on old numbers can cost you opportunities. Fivetran helps by running near real-time syncs and incremental updates, so your warehouse stays up to date without the pain of reloading full tables every time.

3. When you want engineers focused on analytics, not pipelines

• Every engineering team knows how draining pipeline maintenance can be. Fixing schema changes, updating APIs, and patching broken jobs can eat into valuable hours that should be spent on modeling and analytics. Fivetran takes care of those routine chores automatically, letting engineers shift their attention back to delivering insights and building what actually drives the business forward.

4. When compliance and security matter

• Some industries have little room for error when it comes to handling sensitive information. Healthcare and finance, for example, demand compliance with strict regulations. Fivetran is already certified for standards like SOC 2 Type II and HIPAA, and it comes with built-in encryption and secure transfer protocols. This means you get enterprise-grade protection without having to build it yourself.

Signs that you need a Fivetran alternative

Fivetran is often praised for its simplicity and automation, but that does not mean it’s the right long-term fit for everyone. As data volumes increase and use cases become more complex, some recurring issues push teams to explore other options. If you’re noticing any of the following signs, it may be time to consider an alternative.

1. You struggle with connector flexibility

• Pre-built connectors are great for speed, but they are not always built for flexibility. Many users eventually discover that customizing connectors or handling non-standard schemas takes far more effort than expected. Workarounds become the norm, and suddenly the “plug and play” experience feels more like patchwork. 
• So if you’re constantly running into walls when trying to integrate a less common source or tailor a pipeline to your needs, it’s usually a sign that Fivetran is limiting rather than enabling your data strategy.

2. Your data costs keep climbing without clear control

• At first, Fivetran’s consumption-based model seems simple. You pay for Monthly Active Rows, and that scales with usage. But as your business grows, the unpredictability of this model often becomes a pain point. Companies with fluctuating volumes end up facing bills that swing widely from month to month, making it hard to forecast budgets. 
• If a finance team is flagging pipeline costs as unpredictable or unsustainable, that’s a strong signal you might need an alternative with more transparent or fixed pricing.

3. Your workloads are too large for smooth performance

• Fivetran handles mid-sized data needs well, but very large datasets or high-frequency updates can expose its limits. Syncs may take longer than expected, or costs may balloon as you try to keep up with demand. This becomes especially noticeable when analytics teams expect real-time or near-real-time insights and the pipeline struggles to keep up. 
• If performance bottlenecks are delaying decisions or forcing you to trim data just to stay efficient, it shows the platform may not scale as effectively as you need.

4. Support is not keeping up with your needs

• When things run smoothly, support is rarely a concern. But as soon as complex technical issues arise, many teams find that Fivetran’s support feels too slow or too shallow. Waiting on responses or struggling to get detailed help during critical moments can derail entire projects. 
• If your engineers feel like they are troubleshooting on their own, or if delays in resolution are affecting business timelines, it’s often the point where teams start looking elsewhere for a more hands-on support experience.

5. Your use cases require more flexibility

• Fivetran’s strength lies in its wide range of pre-built connectors, but that very strength can feel rigid. If a connector you need is missing, you are forced to build workarounds. The catch? To transform or filter data before it hits your warehouse, you are stuck with the “load then transform” model. 
• Over time, this rigidity becomes a major frustration for businesses with unique pipelines or specialized requirements. If your projects demand more customization, Fivetran’s one-size-fits-all approach may hold you back.

11 Fivetran Alternatives For Better Data Integration Needs

Our research, combining user reviews from G2 and Capterra with detailed assessments of features, pricing, and scalability, has led to this curated list of solutions addressing common Fivetran challenges.

1. Hevo Data – Best for predictable, no-code data pipelines

G2 Rating: 4.4(259)
Capterra Rating: 4.7(100)

Hevo Data offers a comprehensive, no-code ELT platform designed to streamline your entire data pipeline from source to analysis-ready insights. For years, Hevo has empowered users to effortlessly stream data from over 150 sources, providing robust in-flight transformations. 

Hevo is a multi-tenant platform hosted on AWS and is designed to handle billions of records. Furthermore, Hevo offers two data transformation options: drag-and-drop transformations and Python code-based transformations, which offer users flexibility based on choice. Hevo is a very easy-to-use platform and does not require any technical expertise.

Choose Hevo for its blend of ease of use, robust performance, extensive connector library (with the option to request new ones), and transparent, affordable pricing.

Key Features

• No-Code Interface: User-friendly, drag-and-drop setup for fast pipeline creation.
• Auto Schema Management: Handles evolving source schemas automatically, reducing maintenance.
• Seamless Integration with dbt Core: Create, test, and run dbt models directly on Hevo’s platform, leveraging dbt Core’s full capabilities like version control and modular SQL, while potentially avoiding the licensing fees associated with dbt Cloud.
• Pre and Post-Load Transformations: Offers flexibility to clean, enrich, and transform data both before and after loading, using Python or dbt.
• Transparent and Competitive Pricing: Clear, event-based pricing that is often more predictable and affordable than MAR.

Customer Review

Hevo was the most mature Extract and Load solution available, along with Fivetran and Stitch but it had better customer service and attractive pricing. Switching to Hevo has allowed us to boost team collaboration and improve data reliability, and with that, the trust of our stakeholders on the data we serve.

Juan Ramos

Analytics Engineer

Read the full case study here

Pros

• User-friendly drag-and-drop interface simplifies pipeline setup.
• Transparent and affordable pricing, offering better cost predictability.
• Dedicated 24/7 customer support and extensive documentation.

Cons

• Lacks on-premise hosting options (cloud-based only).
• Fewer connectors than Fivetran, but new ones can be requested and are frequently added.
• Primarily focused on data integration; advanced orchestration might require other tools.

Why Choose Hevo Data over Fivetran?

For a more detailed comparison, check out our blog on Hevo vs Fivetran.

Pricing

• Free Plan: Supports up to 1M events per month for 5 users per team
• Starter Pack: Starting at 299$ per month with up to 50M monthly events with SSH/SSL encryption connection.
• Professional Pack: This pack starts at $679 monthly and includes up to 100M monthly events, reverse SSH, and unlimited users.
• Business Critical: If you want to transfer for more than 100M monthly events, you can contact our sales team for a custom quote.

Resources

Documentation | Pricing | Connectors

2. Airbyte – Best for open-source flexibility and custom connectors

G2 Rating: 4.5(47)
Capterra Rating: NA

Airbyte is an open-source data integration platform for ELT, offering extensive customization through its vast connector library. It uses Debezium as an embedded library to capture and monitor changes in your database. Airbyte also provides AI-assisted functionality, which reads through your API documentation and autofills the configuration fields while setting up the CDC pipeline.

One of the unique features of Airbyte is the ability to build custom connectors using their Connector Development Kit (CDK), in addition to the 550+ pre-built connectors that Airbyte provides. Currently, Airbyte supports log-based CDC from Postgres, MySQL, and Microsoft SQL Server to any destination, such as BigQuery or Snowflake.

So, if you are an open-source enthusiast looking for an AI-supported CDC tool with excellent community support, then Airbyte is your go-to platform.

Key Features

• Deployment Options: Self-hosted (free) or managed cloud service.
• Integration with dbt: Supports in-warehouse transformations.
• Flexibility to Develop Python CDC Pipelines: Through PyAirbyte, Airbyte’s open-source Python library, users can develop and manage CDC pipelines in Python.
• Structured and Unstructured Sources: Airbyte supports both structured and unstructured data sources, as well as vector database destinations, making it an ideal solution for AI use cases.
• Self-Managed Enterprise Features: The self-managed enterprise edition of Airbyte provides the capabilities to gain complete control over your sensitive information with features like role-based access control.
• Metadata Tracking: Automatically tracks change metadata (e.g., ab_cdc* columns) to maintain data lineage and facilitate accurate updates.

Customer Review

I really appreciate that Airbyte is open-source and comes with a wide range of pre-built connectors. The UI is intuitive, and the platform makes it easy to configure data syncs. I also like how frequently updates and improvements are made by the team and the community.

Aniruddh S.

Indigo Squad Member

Pros

• Cost-effective due to its open-source core and free self-hosted option.
• Highly customizable, allowing development of new connectors or modification of existing ones.
• Eliminates vendor lock-in.
• Active community support and a growing list of integrations.

Cons

• Steep learning curve, requiring technical expertise (especially for self-hosting).
• Maintenance overhead for self-hosted deployments.
• Cloud offerings can become expensive based on credit usage.

Why Choose Airbyte over Fivetran?

• Better for highly technical teams seeking maximum control
• Offers customization and deep modification of connectors
• Supports cost savings through open-source, self-hosted solutions
• Ideal for unique or rapidly evolving data source requirements
• Unlike Fivetran, does not use a “black-box” approach

For a more detailed comparison, check out Fivetran vs Airbyte

Pricing

• Open Source Edition: Free (self-hosted) with community support.
• Cloud Edition: $2.50 per credit (credits consumed based on data volume and sync frequency).
• Enterprise Edition: Custom pricing for large enterprises needing advanced features and support.

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3. Rivery – Best for end-to-end DataOps with reverse ETL

G2 Rating: 4.7(113)
Capterra Rating: 5.0(12)

Rivery is a SaaS ELT platform offering data integration, transformation, activation, and orchestration capabilities. Rivery also offers reverse ETL, which allows you to sync data from data warehouses to operational systems.

Rivery has pre-built data solution kits that can be used to easily build end-to-end pipelines and data models, without figuring out the technical requirements behind them. For data engineers, Rivery also provides CLI or API to manage, execute, edit, and deploy the data pipelines. Rivery’s acquisition by Boomi is expected to bring the best of iPaaS and AI orchestration, along with data integration and data movement.

If you are looking for an all-in-one solution with multiple features, less coding, and reverse ETL, then Rivery is a good contender.

Key Features

• Centralized Reporting and Logging: A unified dashboard for your entire data flow.
• Workflow Orchestration: Built-in tools to manage complex data flow dependencies.
• Data Transformation: Native transformation capabilities and Python scripting.
• Monitoring & Alerts: Create alerts that automatically help key stakeholders identify and control any issues.

Customer Review

Found rivery to be the most versatile ETL / ELT tool in the market

Ilan R.

Chief Analytics Officer

Pros

• Highly customizable with strong data transformation and orchestration features.
• Built-in version control allowing you to revert changes with a click.
• Separate walled environments for each stage of development.

Cons

• Credit-based pricing can be less transparent or predictable for new users.
• Initial setup for complex workflows might take more time.
• May lack some niche connectors available in larger ecosystems.

Why Choose Rivery over Fivetran?

• Excels where Fivetran is limited in native transformations
• Provides orchestration for managing the entire data lifecycle
• Supports complex transformations and workflow management
• Suitable for organizations needing more than just EL

For a more detailed comparison, check out Fivetran vs Rivery

Pricing

• Starter: $0.75 per credit.
• Professional: $1.20 per credit (volume discounts may apply).
• Enterprise: Custom pricing tailored to specific needs.

4. Talend – Best for enterprise data quality, governance, and hybrid setups

G2 Rating: 4.0(65)
Capterra Rating: 4.6(14)

Talend is a data integration and management platform, with its Talend Data Fabric product suite offering an end-to-end solution. It aims to unify data integration, data quality, and data governance within a single, low-code environment. Talend can handle batch and real-time data streams, generating executable code under the hood.

What distinguishes Talend is its commitment to open-source roots, with Talend Open Studio being a well-known entry point, combined with enterprise-grade features in its commercial offerings. Its ability to generate code from visual designs allows for customization and extensibility.

Talend is suitable for organizations seeking an end-to-end data management solution that spans various deployment models, such as cloud, multi-cloud, hybrid, or on-premises. Data engineers and ETL developers who appreciate a visual development environment but also need the option to delve into generated code or leverage its extensive component library will find Talend versatile.

Key Features

• Flexible Deployment: On-premises, cloud, multi-cloud, or hybrid options.
• Visual Transformation Studio (Talend Studio): Talend Studio provides a graphical, drag-and-drop interface where developers design data integration “jobs” by connecting a vast library of pre-built components.
• Integrated Data Quality Management: A key strength is the tight integration of data quality tools directly within transformation workflows.
• Code Generation and Extensibility: While primarily visual, Talend generates underlying Java or Spark code that can be inspected, customized, or extended by developers needing to implement highly specific logic or integrate custom routines.

Customer Review

UI of Talend Open studio is straightforward to use and understand. Easily users can set up big queries and join the tables, which is amazingly helpful and a time-saver when using big data for operations.

Archana J.

Application Analyst

Pros

• End-to-end solution for complex, enterprise-wide data needs.
• Strong data governance, quality, and compliance features.
• Versatile deployment options catering to various infrastructures.

Cons

• Steep learning curve and may require dedicated IT resources.
• Pricing can be high, making it less suitable for smaller organizations.
• The interface can feel complex compared to newer, more streamlined tools.

Why Choose Talend over Fivetran?

• Ideal for large enterprises needing a full data management suite
• Strong capabilities in data quality and governance
• Supports complex, hybrid environments
• Offers features not natively available in Fivetran

Pricing

• Talend offers several plans (Stitch Data Loader, Talend Cloud Data Integration, etc.) with custom pricing. Contact sales for details.

Check out our detailed blog on Fivetran vs Talend.

5. AWS Glue – Best for serverless ETL within the AWS ecosystem

G2 Rating: 4.2(189)
Capterra Rating: 4.0(9)

AWS Glue is a fully managed ETL service by Amazon that is deeply integrated within the AWS ecosystem. It’s best for organizations heavily invested in AWS, looking for a serverless solution to prepare and load data for analytics.

Glue helps users discover, prepare, move, and integrate data from various sources using a data catalog, visual ETL job authoring, and schedulers. It’s designed for data lakes and data warehouses on AWS.

Choose AWS Glue for its seamless integration with other AWS services (S3, Redshift, RDS), serverless architecture, and pay-as-you-go pricing model, which can be cost-effective for AWS-centric workloads.

Key Features

• Serverless ETL: No infrastructure to manage; scales automatically.
• AWS Ecosystem Integration: Connects natively with S3, Redshift, RDS, etc.
• Data Catalog: Central metadata repository for discovered data.
• Visual and Code-Based Job Authoring: Supports Python and Scala for custom ETL logic.

Customer Review

Absolutly love Glue for its functionality. Provides everything needed.

Sourabh S.

Data Analyst

Pros

Pricing

• Pay-as-you-go, based on Data Processing Units (DPUs) per hour, data catalog storage, and crawlers. Varies by region and job type.

6. Matillion – Best for cloud data warehouse transformations

G2 Rating: 4.4(77)
Capterra Rating: 4.3(111)

Matillion is a cloud-native ELT platform designed to transform data within cloud data warehouses for speed and ease of use. It’s best for enterprises leveraging cloud data warehouses like Snowflake, Redshift, BigQuery, or Databricks, and needing powerful visual transformation capabilities.

It helps data teams load and transform data efficiently using a drag-and-drop interface, accelerating the development of data pipelines. It also supports SQL and Python for custom logic.

Choose Matillion for its intuitive visual pipeline designer and strong focus on in-warehouse transformations, making it highly performant for cloud-based analytics.

Key Features

• Visual ELT Designer: Intuitive drag-and-drop interface for building pipelines.
• Cloud Data Warehouse Optimization: Deep integrations with Snowflake, Redshift, BigQuery, etc.
• Push-Down ELT: Leverages the power of the target data warehouse for transformations.
• Automation and Scheduling: Built-in features for workflow automation.
• Job Designer & SQL Generation: Matillion offers a drag-and-drop interface for building transformation jobs. Users connect components representing various data operations, and Matillion automatically generates the underlying SQL optimized for the target cloud data warehouse.
• SQL and Python Scripting for Extensibility: For custom logic or operations not covered by standard components, Matillion allows users to embed custom SQL scripts directly into workflows via its “SQL Script” component.
• Version Control and Collaboration: Integrates with Git for version control of transformation jobs, enabling team collaboration, change tracking, and rollback

Customer Review

Matillion has all the flexibility and power we need to do the job first time Built-in connectors to heaps of systems; ability to create custom connectors; active community and quick responses to forum questions.

Steve B.

Senior Data Specialist

Pros

• Optimized for fast data loading and complex transformations within cloud data warehouses.
• Intuitive visual designer allows for low-code/no-code pipeline development.
• Strong integrations with major cloud data platforms.

Cons

• Pricing based on credits can become expensive and less transparent at scale.
• Some advanced transformations may still require SQL or Python knowledge.
• Can be less flexible for data sources outside its core integrations.

Why Choose Matillion over Fivetran?

• Visually driven approach to data transformation
• Directly works within cloud data warehouses
• Offers more control for complex transformations
• Often delivers better performance than Fivetran’s post-load model

You can also check out our in-depth review of Fivetran vs Matillion for a more detailed comparison.

Pricing

• Credits-based pricing.
• Basic: Starting at $2.00/credit.
• Advanced: $2.50/credit.
• Enterprise: $2.70/credit.
• (Credits are consumed based on virtual core (vCore) usage per hour).

7. Airflow – Best for orchestrating complex workflows

G2 Rating: 4.3(86)
Capterra Rating: 4.6(10)

Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. It’s best for organizations with strong engineering teams that need a highly customizable and powerful tool for orchestrating complex data pipelines and ETL/ELT processes.

Airflow helps users define workflows as Directed Acyclic Graphs (DAGs) using Python, offering immense flexibility. It’s not an ETL tool itself but an orchestrator that can manage ETL tasks.

Choose Airflow for its unparalleled flexibility in defining intricate workflows, its extensive community support, and its ability to integrate with virtually any system through custom operators.

Key Features

• Programmatic Workflow Authoring: Define complex pipelines using Python.
• Extensible Framework: Large number of community-developed operators and plugins.
• Scalable and Distributed: Can handle a large number of concurrent tasks.
• Rich UI for Monitoring: Visualize DAGs, monitor progress, and manage tasks.

Customer Review

The best thing about Apache Airflow is that it provides integration with various services like big query , AWS , GCP etc.Plus it is available as as service in all cloud provides which provides seamless experience.The User Experience is perfect.

Ashutosh R.

Data Engineer

Pros

• Extremely flexible and customizable, ideal for complex, multi-step workflows.
• Free and open-source with a large, active support community.
• Integrates with a vast array of data systems and tools.

Cons

• Steep learning curve; requires strong Python and DevOps knowledge.
• Not a plug-and-play tool; self-hosting incurs infrastructure and maintenance costs.
• Primarily an orchestrator; data movement and transformation logic often handled by other tools it triggers.

Why Choose Airflow over Fivetran?

• Designed for complex workflow orchestration
• Provides programmatic control over dependencies and tasks
• Supports retry logic and custom task execution
• Offers more flexibility than Fivetran’s simpler model

For a more detailed comparison, check out Fivetran vs Airflow.

Pricing

• Free and open-source. Costs are associated with self-hosting infrastructure or managed Airflow services (e.g., AWS MWAA, Google Cloud Composer).

8. Stitch – Best for simple, budget-friendly replication

G2 Rating: 4.4(68)
Capterra Rating: 4.3(4)

Stitch (acquired by Talend) is a cloud-first ETL service focused on simplicity and ease of use for developers and data teams. It’s best for startups and smaller teams needing a straightforward way to replicate data from common SaaS applications and databases into a data warehouse. Stitch helps by providing a simple interface to quickly set up data pipelines for popular sources, emphasizing ease of onboarding and minimal maintenance for basic ELT tasks.

Along with its simplicity, one of the compelling features of Stitch is its strong data compliance. Stitch’s data source integrations use the minimum permissions that allow read access to necessary data, and can be configured by users to replicate only a subset of available data.

Stitch is favored by engineering teams needing more control, flexibility, and open-source options. Choose Stitch for its transparent pricing, quick setup for familiar data sources, and its focus on core data replication, making it an accessible Fivetran alternative for less complex needs.

Key Features

• Lightweight ETL: Focuses on extract-and-load; no built-in transformations, but you can customize via Singer taps if desired.
• Open-Source Friendly: Integration with Singer and other open tools allows advanced users to extend functionality.
• Scheduled Syncing: Set frequencies (hourly, daily) and let Stitch keep your data up-to-date without manual interventions.
• Developer-Focused: Provides robust APIs and extensibility through Singer taps.
• SOC 2 Certified: Ensures data security and compliance.
• Comprehensive documentation: The Stitch team provides very detailed documentation of their product, and they release every change log on time.

Customer Review

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

Pros

• Simple interface and very quick onboarding process.
• Transparent and relatively affordable pricing for lower data volumes.
• Good for common SaaS sources and databases.

Cons

• Limited number of connectors compared to Fivetran or Hevo.
• Customer support has received mixed reviews, especially for complex issues.
• Less suitable for high data volumes or complex transformation needs.

Why Choose Stitch over Fivetran?

• More cost-effective for startups or small teams
• Simpler solution for basic data replication needs
• Avoids Fivetran’s MAR-based pricing
• Ideal when advanced features are not required

Check out this blog on Fivetran vs Stitch for a more detailed comparison.

Pricing

• Standard: Starts at $100/month (for up to 5M rows/month).
• Advanced: Starts at $1,250/month (for up to 100M rows/month).
• Premium: Starts at $2,500/month (for up to 1B rows/month).

9. IBM DataStage – Best for large-scale ETL and legacy system integration

G2 Rating: 4.0(69)
Capterra Rating: 4.5(2)

IBM DataStage is an enterprise-grade ETL tool designed for complex data integration, transformation, and governance across various environments. It’s best for large organizations with significant investments in IBM technologies or those requiring robust, scalable ETL for on-premises, hybrid, or cloud data.

One of the significant features of DataStage is its Parallel Engine and automated load balancing. DataStage helps manage large-scale data processing with parallel processing capabilities and advanced data quality features. It’s part of the IBM Cloud Pak for Data.

If you’re an enterprise looking for a solution with a powerful parallel engine, extensive connectivity options (including mainframes), and robust data governance features for handling demanding enterprise workloads, IBM DataStage is a strong choice.

Key Features

• IBM DataStage Flow Designer: Increase developer productivity with machine learning-assisted design in a user-friendly interface, helping cut development costs.
• Automated failure detection: DataStage claims to reduce infrastructure management effort by 65%-85 %.
• Broad Connectivity: Supports a wide range of sources, including legacy systems.
• Data Governance Integration: Connects with IBM Watson Knowledge Catalog for metadata and lineage.
• Hybrid Deployment: Runs on-premises or in cloud environments.

Customer Review

IBM InfoSphere DataStage is a stable tool with active support from IBM.\" In fact, many appreciate its straightforward approach \"from a design and development perspective, and also for deployment.

Verified User

Pros

• Effectively handles complex transformations and very large data volumes.
• In-flight data quality maintenance.
• Automated delivery pipelines for production.
• Enterprise-level performance due to its parallel processing architecture.

Cons

• Steep learning curve and a less intuitive user interface for beginners.
• It can be expensive, particularly for smaller businesses.
• Primarily an ETL tool; ELT patterns are less native.

Why Choose IBM DataStage over Fivetran?

• Ideal for large enterprises needing scalable ETL
• Strong transformation capabilities for complex workflows
• Works well with legacy systems
• Integrated data governance with other IBM tools
• More powerful than Fivetran for high-volume transformations

Pricing

Offers various editions (Lite, Standard, Enterprise Bundles) with pricing based on Capacity Unit-Hours or instance costs. Often involves custom quotes.

• Lite: Free plan (limited capacity).
• Standard: Starts around $1.828/Capacity Unit-Hour.
• Enterprise Bundles: Start from $8260/Instance.

10. Meltano – Best for developer-driven, code-first pipelines

G2 Rating: 4.9(7)
Capterra Rating: NA

Meltano is an open-source DataOps platform built around Singer taps and targets, offering a code-first, declarative approach to data integration. It’s best for developer-driven organizations that want full control over their data pipelines and prefer managing configurations in Git (DataOps).

Meltano helps teams build, run, and orchestrate ELT pipelines using existing Singer connectors or by developing custom ones. It emphasizes version control, CI/CD, and a CLI-centric workflow.

Choose Meltano for its open-source flexibility, adherence to DataOps principles, and ability to leverage the extensive Singer connector ecosystem, giving developers fine-grained control.

Key Features

• Code-First & Declarative: Define pipelines in YAML, manage in Git.
• Singer Ecosystem: Utilizes Singer taps (extractors) and targets (loaders).
• DataOps Focused: Integrates well with CI/CD and DevOps workflows.
• CLI and UI Options: Manage pipelines via command line or a basic UI.

Customer Review

I’ve been moving >1TB/day with Meltano for over a year now at a negligible cost; the next best alternative would’ve cost over a million or at least one FTE data engineer. It saves us at least $1M/yr and makes my job easy.

Quinn B.

Machine Learning Engineer

Pros

• Free and open-source, offering significant cost savings.
• Full pipeline control and customization through code.
• Strong integration with DevOps practices (Git, CI/CD).

Cons

• Steeper learning curve, primarily aimed at developers comfortable with CLI and code.
• Being a younger tool, documentation and some features may still be evolving.
• Reliance on community-maintained Singer taps can mean variable connector quality.

Why Choose Meltano over Fivetran?

• Supports a DataOps approach for engineering teams
• Full pipeline control through code
• Leverages the open-source Singer ecosystem
• Offers high customization and developer workflow integration
• Provides more control than Fivetran’s managed service

Pricing

• Free and open-source for self-deployment. Custom support packages are available.

11. Skyvia – Best for SMBs needing easy, wizard-based integration

G2 Rating: 4.8(242)

Skyvia is a cloud-based data platform offering no-code data integration, backup, management, and access solutions. It’s best for small to medium-sized businesses (SMBs) and users with limited technical expertise who need an intuitive, wizard-driven tool for common data tasks.

Skyvia helps connect various cloud applications and databases, automate data replication and synchronization, and perform ETL/ELT operations through a visual interface.

Choose Skyvia for its ease of use, affordable pricing (including a free tier), and broad range of functionalities beyond just integration, making it a versatile tool for SMBs.

Key Features

• No-Code Wizard Interface: Simplifies pipeline creation for non-technical users.
• Versatile Data Operations: Supports integration, backup, and data management.
• Bi-Directional Sync: Can synchronize data between different applications.
• Pre-Load Transformations: Allows data cleaning and transformation before loading.

Customer Review

The platform is intuitive and easy to set up, and it performs reliably for scheduled data jobs and bulk operations. The support team is responsive and genuinely helpful, making issue resolution quick and painless.

Juan V.

System Administrator

Pros

• Very easy to use, even for users with limited technical skills.
• Affordable pricing plans, including a functional free tier.
• Offers data transformation capabilities before loading, unlike Fivetran’s ELT model.

Cons

• Limited scalability for very large enterprise data volumes.
• Fewer connectors compared to more established enterprise tools.
• Customization options may be restricted for highly complex scenarios.

Pricing

Offers multiple tiers:

• Free: Limited features and data volumes.
• Basic: $15/month (billed annually).
• Standard: $79/month (billed annually).
• Professional: $399/month (billed annually).
• Enterprise: Custom pricing.

What are the factors to consider when choosing a Fivetran alternative?

When exploring alternatives to Fivetran, it’s essential to evaluate key factors to ensure the new solution aligns with your business needs. Here are some critical aspects to consider:

1. Security & Compliance

• Look for a platform that meets GDPR, HIPAA, and SOC 2 standards. Fivetran covers the basics, but stricter compliance and strong encryption in transit and at rest can save you a lot of stress down the line.

2. Pricing Structure

• Check whether pricing is predictable. Fivetran’s MAR-based costs can spike as your data grows. A good alternative keeps costs transparent and scalable so your budget doesn’t get blindsided.

3. Connector Availability

• See if the platform supports all the sources and destinations you actually use. Fivetran works for standard apps, but you’ll want something flexible enough to add niche or custom connectors without workarounds.

4. Data Transformation Capabilities

• Look for pre-load or in-pipeline transformation support. With Fivetran, transformations happen after loading, which slows things down. A smarter alternative lets you clean and shape data before it lands, cutting down engineering headaches.

5. Ease of Use & Maintenance

• Ask yourself how much engineering effort setup and maintenance will take. Platforms that are intuitive, well-documented, and easy to manage save your team from constantly fixing broken pipelines.

6. Scalability & Performance

• High-frequency updates or large datasets can expose Fivetran’s performance and cost limits. A scalable alternative will handle growing workloads efficiently, delivering faster syncs and predictable costs even as data volume increases.

7. Support & Community

• Look at support quality and community activity. When complex issues pop up, fast, helpful responses make a huge difference. Fivetran’s support can feel limited for tricky problems, so a more responsive alternative is worth it.

8. Real-Time Processing

• If you need live or near-real-time updates, make sure the tool can handle it. Fivetran mainly offers near-real-time syncs, which may not be enough for operational analytics or dashboards that need fresh data instantly.

Learn More:

• Fivetran vs Striim
• Fivetran vs Mulesoft
• Fivetran vs Azure Data Factory
• Fivetran Review
• Fivetran vs Boomi
• Fivetran + dbt + snowflake stack
• Fivetran vs Xplenty
• Fivetran vs Dataddo
• Fivetran Support
• Fivetran FAQs
  

Conclusion

Choosing the right ETL/ELT tool can be challenging, but we hope this comparison has made it easier for you. Each tool has its strengths and weaknesses, so consider your specific needs, such as data volume, technical expertise, transformation requirements, and budget, when deciding.
For example, if you’re looking for a user-friendly, flexible, and robust data integration platform with transparent pricing and strong support, Hevo Data stands out as an excellent choice. Many users find it to be a compelling Fivetran alternative due to its balance of power and simplicity.
We encourage you to sign up for free trials of your top contenders to experience their capabilities firsthand. 

For Hevo Data, you can Sign up for a 14-day free trial and experience Hevo’s feature-rich suit to see why it could be a better choice than Fivetran for your needs.

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