Top 10 StreamSets Alternatives in 2025

If you’re exploring alternatives to StreamSets, you’ve likely reached a point where your current data integration setup no longer aligns with your goals.

Maybe it’s the rising costs, the heavy maintenance, or the complexity of building and managing pipelines. You might simply be seeking a faster, more scalable way to move data across your systems.

The market has evolved, and modern data integration tools now offer the same performance as legacy platforms like StreamSets, but with a sharper focus on automation, usability, and affordability.

In this article, you’ll discover the 10 best StreamSets alternatives that can help you find the right fit for your requirements.

Don’t want to read the entire article? Here are our top three picks. 

What Is StreamSets?

StreamSets, owned by IBM, is a hybrid and multi-cloud-ready DataOps platform that simplifies building and management of data pipelines across on-premises, edge, and cloud environments.

It is known for its real-time data ingestion and monitoring, allowing you to maintain data quality and reliability across complex pipelines. Its strength lies in handling scalable big data pipelines while giving you visibility into your data flows and pipeline health.

You can automate ETL processes, manage streaming and batch data, and catch errors early. StreamSets is widely used by teams that handle large and dynamic data environments.

Why Are People Moving Away From StreamSets?

StreamSets is a solid platform, but many users face challenges that make it harder to keep up with their evolving data requirements.

1. Expensive pricing

StreamSets charges based on virtual processor core (VPC) at $1,050/ month per VPC. The licensing and infrastructure costs add up quickly, which makes it difficult to scale. This pricing model often feels expensive for smaller or mid-sized teams.

This leads many teams to explore affordable solutions without overrunning their budgets.

What do you dislike about IBM StreamSets? One downside I experienced was performance lag when handling large volumes of data it wasn’t always as fast as I needed. The error logs were sometimes difficult to interpret, especially for more complex issues. Also, while basic tasks were easy to manage, getting into advanced configurations took more time than I expected, and the documentation didn’t always provide clear guidance. Support response times could also be slow when I needed urgent help.

Verified User

Research

2. Slower with large datasets

Often, reports indicate that StreamSets becomes slow with large datasets. This may impact your ability to process, transform, and analyze data efficiently.

If your pipelines need to handle heavy loads or real-time streaming, performance issues can create delays and reduce overall productivity.

What do you dislike about IBM StreamSets? Down sides of using SteamSets might be the cost, for some scenarios the solution might be costlier than the competition, For Large scale data there have been reports of performance issues.

Verified User

Financial Services

3. Limited support

Customers often report a slower response time than expected. When problems arise, timely guidance can be challenging, which leaves teams to troubleshoot complex data issues independently.

With limited documentation to rely on, this increased downtime adds pressure on your internal resources and overall pipeline strategy.

They offer customer support via third party zendesk and their documentation resources aren\'t comprehensive enough in my experience

Pranshu G.

Software Developer

4. Lack of advanced features

StreamSets may not provide all the advanced features you need for modern data workflows. Although it offers a connector library, it is rather limited and might not cater to complex or niche use cases. Missing functionality can limit your ability to customize pipelines, automate processes completely, or integrate with emerging tools.

This often forces you to rely on custom coding or workarounds, which can increase complexity and maintenance overhead.

IBM Stream Sets is a powerful platform, but it can improve in a few key areas. Handling highly complex or customized integrations can be challenging, and connector support for some newer cloud services could be expanded. The learning curve for Control Hub and CI/CD automation is a bit steep for new users, and error messages during pipeline failures could be more detailed to help with faster troubleshooting.

Vivek R.

Data Engineer, Computer Software

Top 10 StreamSets Alternatives to Consider

1. Hevo

G2 rating: 4.4 (271)

Hevo is an ELT and ETL platform that helps you move and prepare data with minimal involvement. It supports over 150 pre-built sources and handles schema mapping with pre- and post-load transformations so your warehouse receives analytics-ready data.

You can onboard Hevo in minutes, set up connectors, and start syncing data without writing integration scripts. This saves you hours that you might spend on setup and maintenance with StreamSets. Additionally, Hevo’s usage-based pricing keeps your budget and efficiency in check.

Key features

• Change Data Capture (CDC) sync: Offers log-based CDC that updates your data destinations instantly as changes occur with minimal latency.
• Responsive customer support: Provides dedicated support through email, live chat, and expert guidance to ensure smooth operations for all users.
• Auto-scaling system: Automatically expands or contracts processing capacity as workloads fluctuate for steady performance without manual tuning.
• Comprehensive resources and templates: Includes detailed guides, pre-built templates, and examples that make it easy to configure data flows and get started quickly.

Pros

• Centralized monitoring for all pipelines.
• Uses at-least-once delivery semantics for minimal data loss.
• Compliant with GDPR, HIPAA, CCPA, and SOC 2 Type 2.

Cons

• Limited on-premise deployment options.
• Custom transformations might require technical help.
• Less flexibility for technical teams.

Pricing

Hevo offers a straightforward pricing model with a 14-day free trial.

• Free: Handles up to 1 million events each month and allows five users.
• Starter: Starting at $239/month, supports 50 million events with SSH/SSL security for 10 users.
• Professional: Begins at $679/ month, covers 100 million events, includes reverse SSH, and unlimited users.
• Business Critical: Custom plans for workloads exceeding 100 million events.

Why should you choose Hevo over StreamSets?

Hevo stands out as an alternative to StreamSets due to its focus on user-friendliness, transparency, and scalability with automated operational features. At the same time, it creates balance by offering complex transformation capabilities with custom SQL. This makes it ideal for teams that want a hassle-free approach with enterprise-level controls.

Customer review

Getting onboarded to the Hevo platform was super easy. I specifically liked the dashboard feature that provides a real-time update on data load status and latency. Hevo’s support is exceptional and we were extremely happy with this product because it exceeded all our expectations.

Emmet Murphy

Staff Software Engineer, Deliverr

Read the full case study here.

2. Fivetran

G2 rating: 4.2 (445)

Fivetran is a fully managed, cloud-based data integration platform designed for hands-off operation and reliable performance. It offers over 700 pre-built connectors, which is ideal for workflows that require niche sources and don’t want the hassle of custom connectors.

It also provides automated schema mapping and real-time monitoring to track pipeline health and ensure data accuracy.

Key features

• Reverse ETL capability: Lets you sync warehouse data back to CRM, marketing, or operational tools for real-time insights.
• Custom connectors: Allows you to request or build connectors for proprietary sources so you can unify all your critical data in one platform
• Complete security: Protects data at every stage with end-to-end encryption, role-based access, and compliance with industry standards, including SOC 2 and GDPR. 
• Flexible destinations: Delivers data easily to a wide range of targets, like cloud warehouses, BI dashboards, and analytics platforms.

Pros

• Excels at batch syncs.
• Supports on-premise and hybrid deployment.
• Guarantees platform availability at 99.9% uptime.

Cons

• Unpredictable pricing that spikes at scale.
• Customer support depends on the plan.
• 1-minute syncs are only available on higher-tier plans.

Pricing

Fivetran charges based on the number of Monthly Active Rows for each connector. The free plan covers up to 500,000 MARs and 5,000 model runs per month. Paid plans start at $500 per million MARs and include a 14-day trial.

Why should you choose Fivetran over StreamSets?

Choose Fivetran if your data team needs speed and scale with minimal oversight. It eliminates pipeline engineering overhead, ensuring analysts get secure, reliable data instantly so you can prioritize rapid business insights.

Customer review

Fivetran has been a valuable tool in our modern data stack. It has helped my team automate most of our data integration needs effectively and efficiently. The pre-built connectors are simple to use and the Fivetran SDK has given us the flexibility to build custom connectors. The support team is responsive and always helps find solutions to our challenges.

DIRECTOR OF DATA ANALYTICS ENGINEERING

3. Airbyte

G2 rating: 4.4 (65)

Airbyte is an open-source ELT platform primarily known for its connector catalog of over 600 pre-built connectors.

You can quickly build and customize new sources using its Connector Development Kit (CDK), which supports any programming language. It’s ideal for teams who are looking for a self-hosted solution with added cloud options.

Key features

• Containerized deployment: Supports Docker-based installations to ensure consistent performance and easy portability across environments.
• Orchestration integration: Connects with tools like Apache Airflow to schedule and manage complex data workflows efficiently.
• AI and ML assistance: Provides AI-driven data mapping and direct integration with vector databases for smarter analytics pipelines.
• Developer API: Enables full pipeline customization through OpenAPI and developer-friendly endpoints for total control.

Pros

• End-to-end encryption with role-based access control (RBAC).
• Strong developer community and contributions.
• Easy migration from legacy ETL tools.

Cons

• Higher infrastructure management overhead.
• Some connectors may be unstable or experimental.
• Occasional delayed updates for new connectors.

Pricing

Airbyte’s self-hosted Core plan is free. The cloud Standard plan starts at $10/month. Business or Enterprise plans offer scalable hosting and advanced governance at custom rates. You can also opt for a 14-day trial.

Why should you choose Airbyte over StreamSets?

Airbyte offers more control than StreamSets and avoids vendor lock-in while scaling your data stack. It supports batch syncs with an open-source model, so you can tailor your pipelines according to your requirements without switching tools.

Customer review

We absolutely love Airbyte. It makes a process that normally has several steps (extract, move the data, format the data, ingest the data, process the data) a simple point and click process. It\'s multiple connectors and ease of use is unparallelled.

IT ASSOCIATE

Banking

4. Estuary Flow

G2 Rating: 4.8 (21)

Estuary Flow is a real-time data integration platform built for teams that need scalable, low-latency pipelines. It supports both streaming and batch processing with under 100ms latency.

It simplifies connecting to various data sources and destinations, and makes setup faster. Estuary Flow also provides visibility into pipeline health with monitoring and alerting features. This makes it a practical alternative for teams seeking efficiency without heavy infrastructure management. 

Key features

• Exactly-once delivery: Guarantees that each data event reaches its destination a single time to prevent duplicates and maintain accuracy.
• In-stream transformations: Applies SQL and TypeScript logic directly in pipelines before data reaches destinations.
• Incremental backfills: Handles continuous updates from historical data without interrupting live data flows or causing downtime.
• Reusable data collections: Send the same dataset to multiple destinations efficiently without reprocessing or creating duplicates.

Pros

• Provides reverse ETL capabilities.
• Offers self-hosted Bring Your Own Cloud (BYOC) setups.
• Affordable pricing.

Cons

• Limited third-party integrations for niche sources.
• Steeper learning curve for complex use cases.
• Lacks extensive community support like open-source alternatives.

Pricing

Estuary offers a free tier that includes 10GB of data and two connector instances each month. Paid plans start at $0.50 per GB with a cap of $100 per connector for up to 12 instances.

A 30-day trial is also available, and plans can be tailored to your specific needs.

Why should you choose Estuary Flow over StreamSets?

Estuary Flow provides you with a single, modern platform that eliminates the operational cost of managing multiple streaming technologies. It provides your team architectural freedom with transactional guarantees and reuse built in.

Customer review

Estuary is easy to configure not just in the UI, but also maintain using their flow documentation specification using CI/CD processes. This means you can do a baseline configuration in the UI and then immediately push that to your programmatic processes. The team is also extremely easy to engage with on their Slack.

James W.

Infrastructure Principal

5. Rivery

G2 rating: 4.7 (120)

Rivery, acquired by Boomi, is a cloud-native ETL platform for teams seeking a low-code solution to automate data workflows. It supports both no-code and code-based pipelines, which makes it suitable for varying expertise.

You get access to over 200 pre-built connectors and the ability to create custom connections for unique sources. Rivery emphasizes automation and monitoring to help teams run scalable data pipelines efficiently.

Key features

• Advanced DataOps and CI/CD: Supports version control and deployment pipelines so data teams can manage development, testing, and production environments with accuracy and consistency.
• Workflow orchestration: Coordinates complex data tasks across multiple systems to keep processes organized and ensure all dependencies execute in the right order.
• Flexible data loading: Offers multiple loading options, including soft deletes and merge strategies, to maintain clean, accurate, and up-to-date records in every destination.
• Reverse ETL: Pushes warehouse data back into business apps and marketing platforms to keep tools aligned with analytics in real-time.

Pros

• Offers data model Starter Kits with templates for common use cases.
• Includes detailed audit logging and metadata collection.
• Inline Python scripting enables powerful, in-platform transformations.

Cons

• Doesn’t support on-premise deployment.
• Graphical interfaces can become confusing with complex workflows.
• The credit-based pricing model is hard to predict. 

Pricing

Rivery’s pricing follows a usage-based model measured by Boomi Data Units. Prices start at $0.90 per unit. Businesses with higher data volumes or enterprise needs can request customized pricing options.

Why should you choose Rivery over StreamSets?

Choose Rivery if you want to manage the entire data lifecycle in a unified cloud-native platform. It helps you unify ingestion, transformation, and activation while promoting strong DataOps practices for better collaboration and control.

Customer review

Rivery by Boomi is an excellent tool that our Data Analytics Team has been leveraging for the past couple of years as our no-code/low-code ETL solution for data ingestion and orchestration. Rivery provides extensive capabilities and monitoring for a fraction of the price of other solutions. This has allowed us to move quickly and easily expand our data warehouse ingestion and ecosystem interactions.

Director of Data Operations

Software

Matillion

G2 rating: 4.4 (81)

Matillion helps you transform and load data directly into cloud warehouses, such as Snowflake, BigQuery, and Redshift. You can use its intuitive interface to build scalable data pipelines without technical expertise.

It focuses on fast, warehouse-native transformations and efficient data orchestration. Hence, it is ideal for teams that operate on cloud-first data workflows.

Key features

• Data lineage visibility: Provides clear insights into data dependencies and transformations for better governance and auditing.
• Custom connectors: Enables you to create integrations with any REST API quickly and reliably.
• Dynamic pipeline jobs: Lets you run parameterized workflows that adapt to changing data inputs and environments.
• Git integration: Integrates directly with Git repositories to manage and version control the entire pipeline for consistent and traceable updates.

Pros

• 1-hour response time on customer queries for higher-tier plans.
• Can be run as SaaS or inside your VPC and VNet.
• Generates and maintains job-level documentation automatically.

Cons

• Advanced features have a learning curve.
• Debugging complex pipelines requires deep log analysis.
• Additional active developer users add to the monthly costs.

Pricing

Matillion charges based on vCore hours, beginning at $2.50 per credit for the Developer plan. Advanced plans come with a minimum monthly commitment and tailored pricing. A 14-day trial is offered for new users.

Why should you choose Matillion over StreamSets?

Matillion handles complex transformations more efficiently than StreamSets, which often needs workarounds. Its pricing suits enterprise budgets, and it’s ideal for teams that value transformation capabilities over a wide connector library.

Customer review

Matillion is a game-changer for data teams. Its intuitive interface makes complex tasks simple, while its power handles massive datasets with ease. Data quality is top-notch, and scalability ensures it grows with your business. Plus, their support is excellent.

Daniel A.

Head of Data Analytics

7. Talend Data Fabric

G2 rating: 4.4 (12)

Talend Data Fabric is a unified platform for managing data integration, quality, and governance across organizations. It helps you centralize, clean, and map data efficiently for analytics and operational use.

It helps you efficiently launch data-driven initiatives, like regulatory compliance projects. Its flexibility also allows you to be cloud-independent with diverse deployment architectures.

Key features

• Data lineage tracking: Visualizes transformations and dependencies across the entire data lifecycle.
• Talend Trust Score: Offers an automated ranking of datasets to guide teams toward the most reliable and high-quality data.
• Change Data Capture: Enables near real-time updates by tracking and synchronizing data changes across systems.
• Data products and marketplace: Creates discoverable and reusable datasets that teams can access, share, and govern across the organization.

Pros

• Supports hybrid, multi-cloud, or on-premise environments.
• Built-in GDPR, HIPAA, and SOC 2 Type 2 compliance.
• Source control and recipe sharing for team collaboration.

Cons

• Steep learning curve.
• Higher cost for small teams.
• Some niche sources need a custom setup.

Pricing

Talend Data Fabric offers a consumption-based custom pricing model where costs are tailored to your workflow requirements.

Why should you choose Talend Data Fabric over StreamSets?

Talend Data Fabric is the ideal choice when your strategy demands complete data certification, not just movement. It provides advanced stewardship and measurable data health across pipelines. This ensures consistent and trusted records for critical business decisions.

Customer review

Talend Data Fabric stands out for its unified platform, open-source foundation, user-friendly interface, scalability, extensive connectivity, and features for data governance and quality. The platform caters to both technical and non-technical users, allowing for flexible and scalable data integration across diverse sources and destinations. It\'s pretty easy to integrate with various data sources.

Siddharth S.

Senior Data Engineer

8. Meltano

G2 rating: 4.9 (7)

Meltano is another open-source option for flexible data pipelines. It supports diverse connectors, including databases and SaaS APIs, for efficient data movement across systems.

Its modular design helps you extend functionality and integrate with tools like dbt for transformation. Meltano emphasizes transparency and developer control. This provides a unified environment for orchestrating and monitoring pipelines without the complexity of traditional ETL tools.

Key features

• Extensive plugin system: Provides a flexible way to add or swap extractors, loaders, and connectors for custom integrations.
• Developer CLI control: Offers full command-line access to run, schedule, and monitor pipelines without relying on a graphical user interface (GUI).
• DataOps workflow: Enables version-controlled pipelines and configurations to promote collaboration and easy rollback for DataOps teams.
• Singer SDK support: Lets you build or extend connectors in Python for quick integration with new or proprietary data sources.

Pros

• Provides on-the-fly data filtering and pseudonymization for PII compliance.
• MeltanoHub offers catalogs for maintained Singer-compliant plugins.
• Supports custom scheduling and workflow integration.

Cons

• Not a low-code or GUI tool.
• Many community connectors have varying quality and maintenance.
• Primarily batch-oriented.

Pricing

Meltano is a free and open-source platform that allows you to self-host. It also offers an Open-Source Support plan with custom pricing for specific requirements.

Why should you choose Meltano over StreamSets?

Meltano provides a Git-native DataOps workflow that treats pipelines as code. It offers version control and collaborative development. It is ideal for technically mature teams valuing vendor independence over managed simplicity.

Customer review

Meltano removes the complexity of creating, maintaining, and running data pipelines. With so many taps and targets pre-built, it feels like Plug’n’Play. Creating custom taps and targets is super easy with the Meltano SDK. All the managerial tasks are handled under the hood, leaving you to focus on getting or consuming the data you need. We estimate a $50k savings by moving a single tap from a well-known cloud competitor to Meltano.

Andy C.

Senior Data Engineer

9. AWS Database Migration Service

G2 rating: 4.1 (49)

AWS Database Migration Service (DMS) is a cloud-native platform ideal for secure and efficient database migrations. It suits organizations moving legacy or on-premises databases to AWS or modern cloud-native systems.

DMS helps you minimize downtime and ensures data remains accurate during migration. It works across multiple database types and provides monitoring to track progress and catch discrepancies.

Key features

• Heterogeneous migration: Facilitates migrations between disparate database engines using the AWS Schema Conversion  Tool (SCT) for object and code conversion.
• Failover support: Automatically switches the replication instance to a standby replica in the event of an outage for continuity.
• Data validation checks: Provides automated tools to verify data consistency row-by-row and support re-synchronization of mismatched records.
• Multi-AZ deployment: Deploys replication instances across multiple Availability Zones (AZs) for maximum resilience.

Pros

• Deep integration with AWS tools like Redshift and Amazon S3.
• Free inbound data transfer for migration from on-premise to AWS.
• Supports CDC replication.

Cons

• Vendor lock-in to AWS infrastructure.
• Does not handle all secondary database objects, like stored procedures.
• Limited transformation capabilities.

Pricing

AWS DMS operates on a pay-as-you-go pricing model. It charges based on replication hours and serverless capacity measured in AWS DMS capacity units (DCUs).

The starting price for a basic serverless migration in the US East (Ohio) region is $0.087/ hour for 1 DCU. Homogeneous migration costs $0.08/ migration hour. Prices vary based on the region.

Why should you choose AWS Database Migration Service over StreamSets?

DMS specializes in database migrations with native AWS integration. It minimizes downtime and ensures data consistency during the move. For occasional database migrations to AWS infrastructure, DMS delivers better cost efficiency and simpler setup than StreamSets.

Customer review

The best features of AWS Database Migration Service include its ease of use, flexibility to support various migration scenarios, automatic schema conversion, and real-time replication capabilities. Additionally, it offers a highly secure and reliable solution for database migration with minimal downtime.

Pavitra M.

Software Engineer

10. Google Datastream

G2 rating: 4.4 (13)

Google Datastream is a fully managed, serverless change data capture and replication service that reliably synchronizes data with minimal latency.

It captures changes from sources like MySQL, PostgreSQL, Oracle, SQL Server, MongoDB, and Salesforce, delivering them to Google Cloud destinations. It is ideal for teams that require continuous synchronization from operational databases to analytics or cloud systems.

Key features

• Unified data type conversion: Transforms source-specific database types into a consistent Avro-based schema for easy downstream processing.
• Secure private connections: Provides Virtual Private Cloud (VPC) peering and Private Service Connect (PSC) options to keep databases off the public internet.
• Automated schema updates: Applies database schema changes automatically to maintain replication without manual intervention.
• BigQuery integration: Delivers data directly into BigQuery using the optimized Write API for real-time analytics.

Pros

• Backfill data is free for the first 500 GB every month.
• Provides granular control over table and column selection.
• Simple UI enables quick replication pipeline setup.

Cons

• Limited to the Google Cloud ecosystem.
• Lacks advanced transformation capabilities.
• Doesn’t support on-premise connectors.

Pricing

Google Datastream’s pricing is based on the volume of data processed. The starting price for ongoing CDC is $2.00/ GiB for the first 2,500 GiB, while the backfill data costs $0.40/GiB after the first free 500 GiB.

Why should you choose Google Datastream over StreamSets?

Choose Datastream if your priority is zero operational management and low-latency replication directly into Google Cloud destinations. Consider that you compromise limited transformation in exchange for full automation.

Customer review

I love it\'s real time data replication which allows for continuous, real time replication of data from various sources to destination and ensure that data is up-to-date. It also supports multiple data sources and destinations. In my case, it helps to connect oracle as source and cloud storage as destination. Also like it\\\'s user friendly UI which hepls easy monitoring and management.

Nikhil N.

Software Developer 2

What Factors Should You Consider When Choosing a StreamSets Alternative?

Selecting the right data pipeline tool isn’t about going for the best one in the market. It’s about ensuring that it aligns with your requirements and resources. Here are some factors to consider when making your decision.

1. Ease of use

You need a platform that your team can adopt quickly without requiring extensive training. Intuitive interfaces, drag-and-drop functionality, or no-code options reduce setup time and make managing data pipelines simpler. However, if you already have a developing team, you can consider self-hosting platforms for more autonomy.

2. Scalability goals

Your data will grow over time, and your platform should grow with it too. Look for solutions that can handle larger datasets, increasing numbers of pipelines, and higher processing volumes without performance degradation or costly infrastructure changes. Scalable tools ensure you won’t need to switch platforms as your business expands.

3. Integration options

Ensure that the alternative tool easily connects with your existing apps, databases, and cloud storage systems. A wide library of prebuilt connectors or the ability to create custom integrations ensures that all your data sources can be unified efficiently. Strong integration options reduce manual work and speed up workflow implementation.

4. Performance and reliability

Slow data processing can cost you a significant amount of time and money. The platform should offer competitive uptime and consistent performance regardless of real-time or batch processing. Reliable tools help you maintain data quality, reduce pipeline failures, and ensure that reporting and analytics are accurate and timely.

5. Pricing and total cost of ownership

Understand the pricing thoroughly before committing to any tool. Evaluate licensing, infrastructure, and storage costs to ensure the tool fits your budget even in the long run. Avoid hidden fees or usage limits that could escalate costs over time. Tools with clear and scalable pricing allow you to plan for growth without financial surprises.

Why Should You Choose Hevo?

Hevo and StreamSets both move data, but Hevo balances the no-code simplicity with enterprise processing. It automates operations, offering monitoring and real-time alerting so you can trust your pipelines are always running.

Hevo also provides flexibility with custom connectors on demand or allows you to create a connector independently through code.

In short, Hevo saves time and money, ensuring that your pipelines run securely and autonomously.

Ready to see the difference? Book a free demo today!

FAQs