5 Best StreamSets Alternatives in 2025 for Real-Time Data Integration

StreamSets is a data integration and pipeline orchestration platform that enables teams to design, deploy, and monitor complex data flows across databases, applications, and cloud services. It has been widely adopted for hybrid and enterprise data engineering.

In July 2024, StreamSets was acquired by IBM and folded into its watsonx data and AI portfolio. While this gives StreamSets the backing of a large enterprise vendor, it also means its roadmap will increasingly align with IBM’s strategy. As a result, many organizations are exploring StreamSets alternatives that offer more agility, lower-latency CDC, simpler operations, or more transparent pricing.

This article compares the five best StreamSets competitors in 2025 — Estuary Flow, Confluent Cloud with Kafka Connect and Debezium, Talend Data Fabric, AWS Database Migration Service (AWS DMS), and Fivetran. Each tool has unique strengths, and the right choice depends on your data latency requirements, deployment model, and integration needs.

Quick Answer: Best StreamSets Alternatives in 2025

The top StreamSets competitors are:

• Estuary Flow – Real-time CDC, exactly-once delivery, and warehouse/lakehouse sync.
• Confluent Cloud with Kafka Connect and Debezium – Managed Kafka backbone for streaming pipelines.
• Talend Data Fabric – Enterprise ETL/ELT with governance, quality, and hybrid deployment.
• AWS Database Migration Service (DMS) – Managed database replication and CDC within AWS.
• Fivetran – Low-maintenance SaaS ELT with 500+ prebuilt connectors.

StreamSets Alternatives: Feature Comparison (2025)

How to Choose the Right StreamSets Alternative

The best StreamSets alternative depends on your latency requirements, CDC needs, and operational model. Use the following checklist to guide your decision:

1. Define latency requirements.
   • Do you need subsecond streaming for analytics and real-time apps?
   • Or are micro-batch or nightly jobs acceptable?
2. Evaluate CDC capabilities.
   • Confirm whether the platform supports insert, update, and delete capture.
   • Look for transactional or exactly-once delivery if data consistency matters.
3. Check connector coverage.
   • Identify the sources (databases, SaaS apps, files) and destinations (warehouses, lakes, streams) you must support.
   • Make sure the vendor’s connector catalog covers them natively.
4. Assess schema handling.
   • Does the platform automatically manage schema drift?
   • Can you enforce data contracts to protect downstream systems?
5. Consider operations and deployment.
   • Decide between SaaS, private cloud, or on-premise.
   • Estimate how much management overhead your team can handle.
6. Understand pricing models.
   • Predict costs using real workloads, not just list prices.
   • Watch for opaque models like MAR (monthly active rows) or scan-based billing.
7. Match to team skills.
   • Teams fluent in Kafka may benefit from Confluent.
   • SQL-first teams may prefer Estuary Flow or Fivetran.
   • AWS-native teams often gravitate to Glue.

Quick takeaway: To pick a StreamSets alternative, define your latency goal, validate CDC depth, confirm connectors, assess schema handling, model pricing under load, and align with your team’s skills. Always run a proof-of-value pipeline before committing.

1. Estuary Flow

Estuary Flow is a real-time data integration platform that unifies what normally requires multiple tools — CDC, streaming, transformations, and delivery. Unlike traditional ETL, Flow is built for low-latency pipelines and transactional guarantees, making it ideal for syncing data continuously between operational databases, data warehouses, and event-driven systems.

Key Strengths:

• Exactly-once delivery through transactional materializations.
• Integrated CDC for Postgres, MySQL, MongoDB, SQL Server, and Oracle.
• Broad destinations: Snowflake, BigQuery, Databricks, Kafka, cloud storage, and open table formats.
• Schema enforcement with automated evolution and validation.
• Time travel & backfill for historical replay and recovery.
• Flexible deployment: SaaS, Private Cloud, or BYOC for compliance/security.
• Subsecond (<100 milliseconds) latency for real-time syncs.

Limitations:

• Advanced features (e.g., schema evolution strategies, transactional materializations) may require some familiarity with streaming and CDC concepts.

Common Use Cases:

• Streaming Postgres or MySQL → Snowflake/BigQuery in real time.
• Replicating MongoDB to Elasticsearch with CDC.
• Replacing Kafka + Debezium stacks with a single platform.

Pricing: 

Predictable, volume-based model: billed per GB of data moved and per active task. This avoids opaque MAR (Monthly Active Rows) or credit-based billing, making costs straightforward to forecast.

Why choose over StreamSets:

Estuary Flow provides simpler operations, subsecond CDC (<100 milliseconds), and transactional delivery, reducing the need for multiple tools while ensuring data integrity. Unlike StreamSets, it also offers exactly-once guarantees and Kafka compatibility without Kafka operations, making it a stronger fit for teams that want real-time pipelines with less overhead and more predictable costs.

👉 Start building for free (no credit card required)

👉 Book a demo to see how Estuary can replace or outperform StreamSets in your environment.

2. Confluent Cloud with Kafka Connect and Debezium

Confluent Cloud is a fully managed Apache Kafka service that eliminates much of the operational overhead of running Kafka clusters. When combined with Kafka Connect (for integrations) and Debezium (for CDC), it becomes a flexible streaming backbone for real-time data pipelines. This architecture is popular with organizations building event-driven microservices and real-time analytics platforms.

Strengths:

• Mature Kafka ecosystem with high scalability and durability.
• Debezium CDC provides low-latency capture for major OLTP databases (Postgres, MySQL, SQL Server, Oracle, MongoDB).
• Large connector marketplace for both open-source and commercial sinks/sources.
• Works seamlessly in event-driven architectures, enabling publish-subscribe and fan-out patterns.
• Integrates with ksqlDB and Flink for stream processing.

Limitations:

• Operational expertise required: users still need Kafka fluency to manage topics, partitions, offsets, and scaling.
• Costs scale with throughput and retention, which can grow quickly in high-volume pipelines.
• Multiple moving parts (Kafka, Connect, Debezium, Schema Registry, sink connectors) must be assembled and monitored for a complete pipeline.
• Not turnkey — lacks the simplicity of managed ETL/ELT platforms.

Use cases:

• CDC from OLTP DBs into Kafka topics, fanned out to multiple consumers.
• Real-time analytics pipelines.
• Backbone for microservices communication.

Pricing: Usage-based (data in/out, partitions, retention).

Why choose over StreamSets: 

Confluent Cloud with Kafka Connect and Debezium is the best choice if your team already standardizes on Kafka and you need a streaming-first backbone with strong CDC support. It provides flexibility and scale, but at the cost of higher complexity and potentially unpredictable spend compared to more turnkey StreamSets alternatives.

For teams that want Kafka compatibility without Kafka operational overhead, Estuary Flow with Dekaf offers an alternative. It exposes Flow collections as Kafka topics, enabling you to keep using Kafka clients, connectors, and the Schema Registry but with the operational simplicity and exactly-once guarantees of Estuary’s streaming platform.

3. Talend Data Fabric

Talend Data Fabric is a data integration and management platform that combines ETL/ELT pipelines with data quality, cataloging, and governance capabilities. It supports both batch and streaming data flows and integrates across a wide variety of on-premise and cloud sources. Talend appeals to large enterprises that need not only pipeline orchestration but also compliance, lineage, and data stewardship features.

Key Strengths:

• Comprehensive toolset: ETL/ELT, CDC, data quality, governance, and cataloging in one platform.
• Hybrid deployment: available as Talend Cloud (SaaS) or self-managed on-prem.
• Extensive connector library for databases, SaaS, and cloud services.
• Strong compliance features: lineage tracking, auditability, and data governance.
• Integrates with modern cloud warehouses (Snowflake, BigQuery, Databricks).

Limitations:

• Higher operational overhead than lightweight SaaS ETL tools.
• Pricing is enterprise-oriented, not always cost-effective for smaller teams.
• Real-time streaming is supported but less mature compared to Confluent or Estuary Flow.
• Learning curve for teams new to Talend’s studio-based development.

Common Use Cases:

• Enterprise ETL/ELT pipelines across cloud and on-prem systems.
• Data governance and stewardship where compliance is critical.
• Migrating or integrating legacy systems into modern data platforms.
• Ensuring data quality and cleansing as part of ingestion pipelines.

Pricing: 

Talend pricing is subscription-based, typically annual, with tiers depending on:

• Number of users and environments.
• Data volume and processing scale.
• Add-ons for governance, cataloging, or real-time streaming.

This makes it flexible for large enterprises, but less transparent compared to volume-based models like Estuary Flow.

Why choose over StreamSets: 

Talend Data Fabric is a good fit if your organization needs more than pipelines — including data quality, lineage, and governance baked in. Compared to StreamSets, Talend offers a broader enterprise data management suite, though it comes with higher costs and complexity.

4. AWS Database Migration Service (AWS DMS)

AWS Database Migration Service (DMS) is a managed service for database replication and migration. It supports both one-time migrations and ongoing CDC (Change Data Capture), making it well-suited for organizations that need to stream data continuously from operational databases into AWS targets such as Amazon Redshift, S3, or Aurora. Unlike Glue, which is batch-oriented, DMS is built to handle low-latency incremental replication.

Key Strengths:

• CDC support for major relational databases (Oracle, SQL Server, MySQL, PostgreSQL, MariaDB).
• Works with heterogeneous migrations.
• Fully managed service — AWS handles provisioning, scaling, and patching.
• Direct integration with AWS analytics and storage services (S3, Redshift, Aurora, Kinesis).
• Can be combined with Glue or Lambda for post-ingestion transformations.

Limitations:

• Best within the AWS ecosystem — limited native support for non-AWS targets.
• Complex transformations are limited; usually requires downstream services.
• Monitoring and troubleshooting large-scale CDC can be non-trivial.
• Pricing grows with replication instance size and data volume, which can surprise teams if not modeled.

Common Use Cases:

• Continuous CDC replication from on-prem databases into AWS Redshift or Aurora.
• One-time migrations for cloud modernization projects.
• Hybrid pipelines, e.g., SQL Server on-prem to S3 for analytics.

Pricing:
AWS DMS charges are based on:

• Replication instance hours (compute size chosen).
• Additional storage for logs and cached transactions.
• Optional data transfer out of AWS (if replicating externally). 

This model is predictable if scoped carefully but can spike during high-change workloads.

Why choose over StreamSets:

Pick AWS DMS if you are all-in on AWS and need database replication or CDC pipelines with minimal setup. Unlike StreamSets, which spans multiple SaaS and on-prem sources, DMS is database-centric and focused on migrations and continuous sync into AWS services.

5. Fivetran

Fivetran is a managed ELT platform best known for its large library of prebuilt SaaS connectors. It automates ingestion, schema management, and maintenance, allowing analytics teams to quickly centralize business data into cloud warehouses like Snowflake, BigQuery, and Redshift. Fivetran is often used to stand up analytics stacks fast without requiring dedicated data engineering resources.

Strengths:

• 500+ SaaS and database connectors with ongoing vendor-driven maintenance.
• Automated schema drift handling, so schema changes propagate with little manual work.
• Low engineering lift: pipelines are configured through UI and API, not custom code.
• Broad ecosystem support for marketing, sales, and finance SaaS applications.

Limitations:

• Latency is measured in minutes, not subsecond — unsuitable for real-time CDC use cases.
• Pricing tied to MAR (Monthly Active Rows) or credit-based billing, which can be difficult to forecast.
• Limited flexibility for advanced or custom transformations beyond simple SQL in the destination.
• Batch-oriented by design, with no exactly-once delivery guarantees.

Use cases:

• Centralizing HubSpot, Salesforce, and marketing data into Snowflake.
• Rapid analytics projects with minimal engineering.

Pricing:

• Monthly Active Rows (MAR): cost increases with the number of rows inserted/updated/deleted each month.
• Credit-based plans: credits are consumed based on volume and connector activity.
  This model provides elasticity but can make cost forecasting unpredictable, especially with high-change-rate datasets.

Why choose over StreamSets: 

Fivetran is ideal if you need fast SaaS ELT pipelines with minimal setup and can accept minute-level latency. It’s best suited for analytics teams that want quick access to SaaS data in a warehouse, but not for real-time CDC or operational pipelines.

Which Alternative Should You Pick?

• Need subsecond CDC with exactly-once guarantees and simpler operations? → Estuary Flow
• Already standardized on Kafka and want a streaming backbone? → Confluent Cloud with Debezium ( If you want Kafka compatibility without the ops overhead, consider Estuary Flow with Dekaf)
• Need enterprise ETL with data governance and hybrid deployment? → Talend Data Fabric
• All-in on AWS and need managed CDC replication? → AWS DMS
• Need SaaS connectors fast with low setup effort? → Fivetran ( If you also want to sync databases + SaaS apps in real time, Estuary Flow can cover both in one platform)

Conclusion

StreamSets remains a capable data integration platform, but in 2025, many teams need lower-latency CDC, simpler operations, or more transparent pricing than it provides. Depending on your use case, alternatives like Confluent Cloud, Talend, AWS DMS, and Fivetran may fit.

But if you’re looking for real-time CDC with exactly-once delivery, subsecond (<100 ms) latency, and predictable volume-based pricing, Estuary Flow stands out as the strongest StreamSets alternative.

Ready to Try Estuary Flow?

Estuary Flow unifies CDC, streaming, and ETL into one real-time platform — with subsecond (<100 ms) latency, exactly-once delivery, and transparent volume-based pricing. Whether you’re moving data from databases, SaaS apps, or streams, Flow simplifies what StreamSets and other alternatives make complex.

• Sign up for free — start building pipelines today, no credit card required.
• Book a demo — see how Estuary can fit your use case.
• See customer success stories — learn how teams like yours are using Flow.
• Join our Slack community — get help, share use cases, and connect with other data engineers.