Best Apache NiFi Alternatives to Consider in 2025

You are probably here because you are either using Apache NiFi for your data integration workflows or just exploring it as an option because of its visual interface, open-source nature, and flow-based design. It is a solid tool for many data ingestion tasks, especially if you’re working with on-premise systems or batch-based pipelines.

But here’s the thing: someday your data needs are going to change. Let’s say you want to scale or evolve, or say you now want to move to the cloud, start streaming data, or you need to build a more robust data architecture. At this point, Apache NiFi might start to feel more like a bottleneck, and you are probably already there.

In this guide, we’ll walk you through the top Apache NiFi alternatives in 2025 that are making waves in the ETL/ELT and data integration space. Whether you’re seeking better performance, smoother UI/UX, more modern cloud support, or just want to avoid maintenance headaches, we’ve got you covered. Let me break down the features, pricing, real user feedback, and when it makes sense to switch.

What is Apache NiFi?

Apache NiFi is an open-source data integration tool. It is designed to automate the flow of data between the systems. It is built on a flow-based programming paradigm. It allows users to define a series of processors, represented as nodes in a flow, that ingest, transform, and route data across various source and destination endpoints.

It has a drag-and-drop interface, which makes it relatively easy to build and monitor pipelines visually. It’s particularly effective for on-premise architectures, offering greater control over how data is processed. 

NiFi is best suited for engineering teams who prefer more control over infrastructure and are comfortable managing self-hosted environments. However, while it’s powerful, it does have its challenges, which is why many teams start looking for alternatives as their needs change.

Why Are People Moving Away from Apache NiFi?

Let us look at some of the most common fallbacks, backed by some real user feedback from review platforms like G2 and Capterra:

1. Steep Learning Curve and Complex Setup

Yes, Apache NiFi is a “low-code” platform, but it’s definitely not “no-code”. Users sometimes struggle with setting up complex pipelines, especially when working with something custom to their business requirements, nested processors with advanced flow logic. This brings in an entry barrier for non-engineering team members.

“NiFi has a high learning curve, especially when it comes to understanding how data flow works at scale. The UI helps but doesn’t abstract away the complexity.” – G2 Review

2. Performance Bottlenecks at Scale

As NiFi generally runs in a self-managed environment, it’s painful to configure and maintain when scalability for processing real-time, high-volume, and streaming data comes into the picture.

“We faced major throughput issues as data volume grew. NiFi just wasn’t built for high concurrency in the cloud.” – Capterra Reviewer

3. Limited SaaS Integrations Natively

Yes, Apache NiFi is extensible with data connectors. However, it lacks native plug-and-play connectors for popular SaaS applications. Due to this, you would often need to do some custom development with an increased maintenance overhead.

“The list of out-of-the-box connectors is small. We had to write custom code to integrate with tools like HubSpot, Snowflake, or Salesforce.” – G2 Reviewer

4. Not Built for Cloud-Native Environments

Not a cloud native tool, even though you can host it on a self-managed cloud mode. Cloud native features like scaling nodes, automated deployments, and ensuring high availability with modern orchestration often require manual tuning.

“Running NiFi on Kubernetes wasn’t as smooth as we expected. It feels like a tool designed for on-premises, not the cloud.” – Capterra Reviewer

Top 5 Apache NiFi Alternatives to Consider

Here’s a quick comparison table to give you a snapshot before we dive into the full breakdown:

Tool	Best For	Key Advantage	Starting Price
Hevo	Saas Integration, real-time data pipeline with CDC capabilities.	No-code, with a code base option and fully managed, real-time streaming	Free tier available(free up to 1 million events per month)
Fivetran	Automated ELT for analysts	Robust connector library, easy setup	Starts at $0 (usage-based)
Stitch	Lightweight ELT, best for small projects with small teams.	Simple and fast to implement	Free plan available
Integrate.io	ETL & reverse ETL for cloud-first teams	Drag-and-drop pipeline builder	Custom pricing
Keboola	Modular data stack for advanced users	Built-in orchestration, sandbox environments	Pay-as-you-go
Airbyte	Open-source ETL with a large connector base	Highly customizable, open core	Free (self-hosted)

1. Hevo – A Modern, No-Code Alternative to Apache NiFi

If you’re looking for a platform that just works, with no complex setup, no maintenance headaches, and real-time data delivery, Hevo is the answer.

Unlike Apache NiFi, Hevo is a no-code, cloud-native ELT platform that allows you to replicate data in real time. It’s trusted by teams across industries to streamline their analytics and eliminate data silos, without writing a single line of code. 

Hevo is designed for SMBs and mid-market companies looking for fast setup, reliable data pipelines, and strong support. And yes, Hevo is actively building tighter support for dbt, too.

Key Features:

1. Real-time data synchronization:

You get the support for continuous data integration and replication with minimal latency, keeping your analytics up to date, with its built-in change data capture (CDC) capabilities.

2. Automatic Schema Mapping and Evolution:

Hevo data integration flow automatically detects a change or any drift in the schema of the data flowing through the pipeline. It then adjusts to the schema change in source systems, minimizing pipeline breakage along with mapping the sink accordingly.

3. Wider data connector ecosystem:

Hevo allows you to connect to various popular data sources, including databases, SaaS applications, event streams, and cloud storage. It enables you to integrate using its zero-maintenance, rich plug-and-play connectors. It has around 150+ connectors to date.

4. Built-in data transformation:

It has a wide range of built-in transformations that you can use out of the box. It enables transformation using a visual interface or SQL for cleansing, filtering, and aggregation before delivering it to the sink.

5. Error Handling and Monitoring:

Hevo comes with a comprehensive dashboard for log and alert monitoring. This helps you expand visibility and quick troubleshooting on the running data pipelines. 

6. Robust Data Quality & Governance

Hevo includes built-in data validation and monitoring features to catch pipeline failures or anomalies early. It also supports role-based access control and detailed audit logs to meet enterprise security standards.

7. Transparent Pricing & Enterprise Support

Hevo’s pricing is usage-based and straightforward, with no hidden costs for connectors or users. It has a dedicated customer success team helping enterprises design, deploy, and scale data workflows confidently.

“Hevo’s no-code interface helped us save engineering bandwidth and enabled our analysts to set up pipelines independently. Real-time sync just works.” — G2 Review from a Growth Manager at a FinTech startup

Pros:

• Beginner user-friendly UI
• Fully managed with no infrastructure overhead.
• Clear, concise documentation with a proactively fast support team.
• Easy to maintain with minimal to no technical skills required.

Cons:

• Limited flexibility for advanced transformations compared to open-source tools.
• You can’t deploy it on on-prem servers, it is a cloud-only solution.

Why Choose Hevo Over Apache NiFi?

• Cloud native with no need to provision servers or manage clusters.
• Hassle-free real-time pipelines.
• Faster time to value. Onboard in just a matter of minutes to run managed data pipelines.

Pricing:

Hevo offers a free tier for up to 1 million events per month. It’s paid plans only start as you scale. Pricing is usage-based and transparent without any billing surprises.

2. Fivetran –  A Plug-and-Play ELT Powerhouse

Fivetran is a cloud-based ELT tool designed specifically for enterprise teams. It helps in building fully managed and automated data pipelines with minimal manual interventions. Reliability and simplicity are the core of this platform. 

Compared to Apache NiFi, which requires custom flow design and cluster management, Fivetran completely abstracts infrastructure and maintenance. It’s widely used by mid-to-large enterprises with mature data stacks, but its ease of use makes it approachable for small teams too, provided budget isn’t a major concern. It’s particularly popular among companies needing maintenance-free data integration workloads.

Key Features:

1. Production-ready data connectors.

Offers a wide range of plug-and-play connectors. Its extensive connector library with around 200+ connectors lets you integrate databases, SaaS, event streams, marketing platforms, etc. These connectors are built within the platform and don’t need any manual maintenance.

2. Automated schema evolution and data drift.

Fivetran automatically catches any changes in the schema of the data at the source. It monitors data drift and handles downstream processes with little to no impact on the data integration pipeline.

3. Change data capture (CDC) support.

Natively supports change data capture (CDC) capabilities. It helps in sync of only the changed data to optimize efficiency and reduce latency.

4. Role-based access control and audit logs.

The RABC (Role-Based Access Control) mechanism in Fivetran helps you keep data governance in place, allowing restrict access to internal company resources and manage permissions within each resource area.

5. Data Normalization

It has an in-built feature to standardize and transform raw post-integration data for cleaner analytics.

“It’s the closest thing to set-it-and-forget-it. But it gets expensive fast as your data volumes grow.” — G2 Review from a Senior Data Engineer at a SaaS company

Pros:

• Extremely reliable and hands-off once configured, set it once and forget it.
• Broadest connector ecosystem in the market.
• Excellent data integrity and automatic schema updates.
• Enterprise-grade security and compliance.
• Wide range of enterprise-grade connectors.

Cons:

• Pricing can become prohibitive for high-volume or fast-growing datasets. Entry barrier for startups or low-volume users.
• Limited transformation flexibility without dbt or external tools.
• Less transparency on internal sync processes compared to open-source tools.

Why Choose Fivetran Over Apache NiFi?

• Hosted, managed, and always up to date.
• More breadth and quality than DIY integrations in NiFi.
• No XML flows or server tuning, just connect and sync.

Pricing:

Fivetran uses an “active row” pricing model, which can be difficult to estimate and sometimes leads to surprise bills. No free tier is available, but there is a 14-day trial for most connectors.

3. Stitch – A Lightweight, Budget-Friendly ELT Tool

Stitch is a cloud-native ELT platform. It is tailored for small and medium-sized businesses and startups. It provides a straightforward and affordable mechanism to move data across various data locations, data warehouses, and lakes. It is built on top of the open-source Singer Framework, making it highly extensible and customizable.

When compared to Apache NiFi, Stitch prioritizes simplicity and ease of use over complex flow orchestrations. It’s designed for fast, hassle-free data ingestion pipelines. It is a favourite tool for teams and organizations with modest data volume who want to quickly get the data flowing without heavy engineering investment.

Key Features:

1. Simple data management pipeline

It comes with a very user-friendly interface. A Simple User Interface makes it easier to manage and monitor data pipelines with minimal fuss.

2. Open-Source connector Ecosystem

Built on top of the Singer Framework, helps you in leveraging a wide range of data connectors using Singer taps, including but not limited to databases, SaaS applications, and event streams.

3. Automatic schema evolution:

Automatically optimizes the data integration to adjust the changes in the schema at the data source.

4. Inbuilt Transformations

It comes with basic transformations using Singer-compatible scripting.

5. Job scheduling

Stitch comes with a cron-based scheduler out of the box. You can use it for easy job scheduling and load control.

“It was an OK experience. I works well but just lacks features that other tools offer for the same price.” — Capterra Reviewer, Data and Analytics Manager

Pros:

• Very easy to set up and use. Friendly to users without a data engineering background
• Transparent pricing model (consumption-based). Also has a free tier plan.
• Quick to onboard and easy to use.
• Lightweight ELT tool.

Cons:

• Doesn’t support CDC out-of-the-box.
• Lacks robust transformation logic
• Lacks advanced orchestration and monitoring features.

Why Choose Stitch Over Apache NiFi?

• No servers, clusters, or flowfiles to deal with, like we need to do in Apache NiFi.
• Stitch is built for simplicity and speed-to-value, good for startups.
• Supported by the open-source community.
• More accessible to non-engineers than NiFi

Pricing:

Starts at $100/month for up to 5 million rows, with incremental pricing as data volumes grow.

4. Integrate.io – No-Code ETL & ELT

Integrat.io (formerly Xplenty) is a hybrid ETL and ELT platform. It is designed to streamline data integration across cloud warehouses, SaaS applications, etc. It is built for teams that need a visual, no-code/low-code environment to build complex pipelines.

It’s particularly strong at combining, transforming, and enriching data from multiple sources before loading it into a cloud data warehouse. It’s an ideal choice for the data teams that want the power of custom transformations without writing much code.

Key Features:

1. Drag and Drop visual editor:

You can leverage the drag-and-drop feature of the platform to design and orchestrate simple to complex workflows. Visual editor can help you combine multiple data sources, programmatic branching logic, and transformation, all without writing a single line of code.

2. Supports both ETL and ELT workflows:

You can run both ETL to the warehouse or ELT to data lake workloads. This makes it ideal for modern data workloads.

3. Extensive data connector library:

You can leverage its wide range of data connector libraries to connect to popular databases, SaaS applications, cloud storage providers, etc.

4. In-platform transformation:

You can perform data cleaning, filtering, joins, aggregations, and scripting using either SQL or JavaScript without even needing to leave the platform.

“Integrate.io offers a flexible and adaptable solution that can be tailored to satisfy the unique requirements of various enterprises and sectors.” — G2 Reviewer, Senior Data Scientist at First Republic Bank

Pros:

• Visual builder makes it easier for non-technical users
• Robust transformation layer built into the platform
• Job scheduling and orchestration, logging, along with monitoring features, out-of-the-box.

Cons:

• Limited control over very complex, performance-optimized pipelines
• Pricing can be less predictable for high-volume users
• Real-time streaming support isn’t as deep as specialized platforms

Why Choose Integrate.io Over Apache NiFi?

• Easier for business users and analysts to operate
• No need to worry about cluster configuration or security patching
• Combines ETL, ELT, and API management in one tool

Pricing:

Custom pricing based on a number of connectors, data volume, and usage. Offers a 14-day free trial with full feature access.

5. Keboola

Keboola is a unified data platform, built with DataOps in focus. It provides a unified workspace for data engineers, analysts, and operations teams to collaborate on data pipelines. 

Unlike Apache NiFi, Keboola offers a modular platform that combines ETL, orchestration, and operational analytics with powerful API integration. It’s best for modern teams looking to automate and document data workflows, from extraction to insights, with greater governance and transparency.

Key Features:

1. Centralized Data Management Platform

Kebola features a complete package to manage data ingestion, transformation, orchestration, and delivery, covering the entire data lifecycle.

2. Visual pipeline builder

It has a rich visual drag-and-drop workflow design feature. It helps both tech as well as non-tech people to build robust data pipelines. In addition to this, it comes with the flexibility to add SQL, Python, or R scripts for custom transformations within the same workflow.

3. Built-in version control and collaboration

You can manage environments based on files (development, staging, and production) using its built-in version control system. It adds to the simplicity of collaboration within and across cross-functional teams.

4. Pre-built connectors and API integrations

It has a rich ecosystem of built-in connectors and direct API connectors. You can connect to databases, SaaS applications, cloud storage, and BI tools within a jiffy. 

5. Advanced Data Governance and Security

It enables you to keep data governance and security in check, with fine-grained access control, auditing, and compliance features with enterprise readiness.

“The thing I like the most about keboola is the fact that just by signing in, I can start doing my work even on a brand new client without worrying about installations, infrastructure discussions, etc.” — Capterra Reviewer, CEO Information Technology and Services

Pros:

• Excellent for collaborative, multi-role data teams
• Built-in version control ensures traceability and rollback
• Native support for advanced tools like dbt and Jupyter

Cons:

• It may be overwhelming for small teams without a defined data ops process
• UI has a learning curve compared to more simplified tools
• Custom connector support is slightly limited

Why Choose Keboola Over Apache NiFi?

• Designed for entire data teams, not just engineers
• No operational overhead
• Ideal for teams needing auditability and governance

Pricing:

Offers a free tier with limited compute/storage. Paid plans start with flexible pay-as-you-go options based on usage and team size.

Factors to Consider When Choosing an Apache NiFi Alternative

Let us now discuss some essential factors that you should always evaluate whenever you are either making a switch or evaluating a data integration tool:

Integration Capabilities

Does the tool natively support data integration to all your current as well as probable future data sources, like SaaS apps, cloud databases, APIs, and file systems?

Always prioritize the tools that let you plug into your stack with the least engineering overhead.

Transformation Flexibility

With pre-built transformation available across different tools. Sometimes we have different transformation logics unique to our business. For this, ask the question: does the tool let you run custom SQL or Python transformation, or even dbt with any custom logic for your data workflow?

Performance & Scalability

Make sure that the tools support parallelism, change data capture (CDC), and streaming-first architectures.

Data Governance and Security

For regulated industries or sensitive data, you’ll need fine-grained access controls, audit trails, data masking, and compliance certifications (GDPR, HIPAA, SOC 2). 

Ease of Use and UI

A complex UI or steep learning curve can slow down your team. So, to move faster in the market, look for modern tools that focus on a low-code/no-code interface with visual pipeline builders and guided setup flows.

Support & Documentation

Robust customer support and active documentation can make or break your onboarding experience. Do consider:

• Does the platform offer 24/7 support or dedicated solutions architects?
• How responsive is the team on forums or email?
• Are real-world examples available in the docs?

Pricing Transparency

Many teams outgrow NiFi because the operational cost of maintaining it increases with scale. When evaluating alternatives, look for:

• Clear, usage-based pricing models
• Free tiers for testing and PoCs
• No hidden charges for connectors, users, or orchestration

Conclusion

Data pipelines start at the data integration layer, and the choice of the right tool in today’s fast-moving data landscape can either make or break your data strategy. While Apache NiFi has its strengths in flexibility and visual flow design, it may not always be the best fit, especially for teams prioritizing ease of use, scalability, or lower maintenance overhead. 

Exploring alternatives like Hevo, Fivetran, and Stitch can help you find the balance between power and simplicity. The key is to align your tool choice with your team’s capabilities, data volume, and long-term goals.

Looking for a simpler, no-code way to automate data pipelines? Try Hevo Data—a fully managed solution that lets you seamlessly integrate and transform data without the complexity. Sign up for a 14-day free trial. 

Frequently Asked Questions About Apache NiFi Alternatives