Rivery, founded in 2019 and recently acquired by Boomi, is a public cloud ELT platform with features like inline Python transforms, reverse ETL, and workflow orchestration. While it offers some real-time CDC at the source, its architecture relies on batch loading, with minimum destination intervals of 60, 15, or 5 minutes depending on the plan.
For teams seeking lower latency, more flexible deployments, or modern real-time architecture, several strong alternatives have emerged in 2025. In this guide, we’ll explore five top Rivery alternatives: Estuary Flow, Fivetran, Matillion, Striim, and Talend, highlighting their features, advantages, and what to consider.
Top 5 Rivery Alternatives in 2025
Looking for a more flexible, real-time alternative to Rivery? These five platforms offer faster pipelines, better deployment options, and greater scalability.
1. Estuary Flow
Estuary Flow is a modern data integration platform purpose-built for both real-time streaming and batch ETL/ELT. Founded in 2019 and built on a decade of streaming experience via the open-source Gazette project, Estuary is the only vendor in this comparison that truly combines sub-second latency, exactly-once CDC, and multi-target delivery in a single pipeline.
It shines in scenarios involving change data capture (CDC), low-latency replication, multi-destination fanout, and complex transformation logic, all with the ability to scale to multi-GB/sec throughput. It’s also the only platform in this group offering private cloud deployment, allowing dedicated compute in your own cloud account, managed via a shared control plane — the best of both on-prem and SaaS.
Key Features of Estuary Flow
- Sub-100ms latency with exactly-once CDC from transactional logs (WAL-based), not batch polling.
- Streaming and batch pipeline unification: Use a single pipeline to capture and fan out data to multiple real-time or batch destinations.
- Transactional collections architecture for reliability, backfill, and schema evolution — every change is captured once and available for any number of downstream targets.
- Flexible transformations using SQL, TypeScript (and soon Python), plus support for dbt for ELT workflows.
- Connector ecosystem: 150+ high-performance native connectors, plus support for 500+ Airbyte, Meltano, and Stitch connectors (with validation).
- Deployment options: Public SaaS, Private Cloud (dedicated managed plane), or self-hosted under an open source license.
Key Benefits of Estuary Compared to Rivery
- Truly real-time: Estuary achieves sub-second latency with minimal source load, unlike Rivery’s 5–60 min batch intervals using Kafka-based file streaming.
- Most efficient CDC: Estuary avoids putting stress on database WALs, ensuring high reliability and avoiding failure-prone batching patterns used by Rivery and ELT tools.
- Lowest cost at scale: Estuary consistently outperforms other vendors on cost at all volumes, especially important when syncing to multiple destinations.
- Most flexible deployment: Estuary uniquely supports Private Cloud (dedicated but SaaS-managed), SaaS, and self-hosting — Rivery is public SaaS only.
- Reliable delivery: Exactly-once, transactionally guaranteed pipelines ensure you never miss or duplicate data across streaming, analytics, or AI use cases.
- DataOps-friendly: Customers often report 4x productivity gains due to ease of setup, low maintenance, and powerful debugging and schema tooling.
Learn more: Estuary vs Rivery
2. Fivetran
Fivetran is one of the most established players in the ELT space, known for its fully managed SaaS platform and a wide array of pre-built connectors. It excels at syncing data from SaaS tools and databases into cloud data warehouses with minimal setup. However, it is fundamentally batch-based and designed primarily for enterprise-scale data replication rather than low-latency or real-time workloads.
Key Features of Fivetran
- Extensive connector catalog with 300+ integrations, including Salesforce, NetSuite, Stripe, and PostgreSQL.
- Managed change data capture (CDC) for databases like Postgres, MySQL, and SQL Server.
- Automated schema migration to keep destination tables in sync with source changes.
- Integrated dbt transformations, enabling users to manage models directly from within Fivetran.
- Strong focus on reliability and governance, with features like data lineage and usage tracking.
Considerations for Fivetran
- Cost at scale: Fivetran’s usage-based pricing (based on MAR — monthly active rows) can become prohibitively expensive as data volumes or row changes grow, even compared to Rivery.
- Latency limitations: While Fivetran offers CDC for certain sources, the data is typically loaded in batch intervals (e.g. every 5 minutes or longer). It does not provide true streaming or sub-second updates.
- Public cloud only: Fivetran is a fully managed service with no self-hosted or private deployment options. It is similar to Rivery but more limited for enterprises with strict infrastructure requirements.
Learn more: Rivery vs Fivetran
3. Matillion
Matillion is a cloud-native data integration platform that offers both ETL and ELT capabilities with a strong focus on data transformation inside cloud data warehouses like Snowflake, BigQuery, Redshift, and Databricks. It provides a visual job builder combined with SQL-based logic, making it accessible to data engineers and analysts alike. Matillion is widely adopted in mid-sized to large organizations looking to orchestrate complex pipelines in warehouse-centric environments.
Key Features of Matillion
- Visual job orchestration: Drag-and-drop interface for designing ETL/ELT workflows with components for scripting, branching, and transformation.
- Built-in connectors: Connects to popular data sources and supports push-down ELT for warehouses (e.g. Snowflake, Redshift, BigQuery).
- SQL-first transformations: Offers flexibility for advanced users to customize pipelines using native SQL.
- DevOps integrations: Supports Git, CI/CD pipelines, and environment management for collaborative development.
- Matillion ETL vs Matillion Data Productivity Cloud: Offers two products — the traditional ETL tool and a newer SaaS platform focused on collaborative data workflows.
Considerations for Matillion
- Primarily batch-oriented: While it supports automation and scheduling, Matillion doesn’t offer real-time CDC or streaming, making it unsuitable for use cases requiring sub-minute latency.
- Deployment complexity: Users must choose between managing infrastructure (VMs on AWS/Azure/GCP) or using the SaaS version. Setup and scaling can be more hands-on compared to fully managed tools like Rivery or Estuary.
4. Striim
Striim is a real-time data integration and streaming analytics platform purpose-built for low-latency, high-throughput data movement. It’s well-suited for enterprises with demanding operational and analytical workloads that require continuous data flow from databases, cloud services, and message queues to modern destinations. With rich in-flight processing and exactly-once guarantees, Striim positions itself as a streaming-first alternative to batch-based ELT tools like Rivery.
Key Features of Striim
- Real-time data capture with low-latency ingestion from databases like Oracle, SQL Server, MySQL, and PostgreSQL.
- In-flight stream processing: Apply filters, transformations, and aggregations on data in motion.
- Exactly-once delivery: Ensures data integrity across distributed systems.
- Rich connector ecosystem: Includes sources and targets like Kafka, cloud storage (S3, Azure Blob), messaging systems, and data warehouses.
- Enterprise scalability: Built for high availability, fault tolerance, and large-scale distributed deployments.
Considerations for Striim
- Complex pricing model: Striim’s subscription pricing depends on data volume, source/target count, compute usage, and features. Costs can add up quickly, especially for smaller businesses or teams with unpredictable workloads.
- Vendor lock-in: Striim is a proprietary platform with limited open-source exposure. Migrating away can be difficult once embedded into core pipelines.
- Limited openness: Unlike open-source tools such as Kafka or Debezium, Striim provides less transparency and extensibility for engineering teams wanting fine-grained control.
5. Talend
Talend is a long-established data integration platform that combines ETL, data quality, governance, and transformation capabilities. Once known for its open-source roots, Talend is now part of Qlik (acquired in 2023), and its platform is positioned more toward enterprise-grade data management than lightweight data movement. It’s ideal for large organizations needing comprehensive control over data quality, lineage, and compliance, but is less suited for real-time or streaming use cases.
Key Features of Talend
- Integrated data platform: Combines ETL, data profiling, quality, stewardship, and cataloging in a single environment.
- Support for hybrid and multi-cloud: Works across on-prem systems, cloud providers (AWS, Azure, GCP), and SaaS sources.
- Flexible development options: Offers both a visual low-code interface and Java-based scripting for custom integrations.
- Strong governance features: Built-in metadata management, auditability, and lineage — ideal for compliance-heavy industries.
- Deployment options: Available as SaaS (Talend Cloud) and self-hosted on VMs or Kubernetes for regulated environments.
Considerations for Talend
- Not real-time or streaming-first: Talend remains fundamentally batch-based, which limits its ability to support sub-minute latency or continuous pipelines — a key need in modern real-time architectures.
- Heavyweight and complex: The platform’s breadth is a strength for governance, but it also means higher complexity, steeper learning curves, and longer implementation cycles compared to tools like Estuary or Rivery.
Conclusion
While Rivery has carved out a niche as a modern ELT platform with Python transforms and workflow orchestration, its batch-first architecture, public-cloud-only model, and limited real-time capabilities make it less suitable for organizations seeking low-latency, scalable data integration.
In 2025, the data landscape demands more flexibility, speed, and reliability. Tools like Estuary Flow are leading the next generation of pipelines by unifying streaming and batch, enabling true CDC, and supporting multi-destination delivery — all with sub-second latency and exactly-once guarantees. Fivetran and Matillion continue to serve traditional ELT use cases well, while Striim and Talend offer depth in streaming and governance, respectively.
The right alternative ultimately depends on your priorities: real-time performance, deployment flexibility, cost at scale, or data governance. But for teams looking to future-proof their data stack, especially with AI, real-time analytics, and operational use cases in mind, Estuary Flow stands out as the most forward-looking option.
Getting Started with Estuary
Ready to try a truly real-time alternative to Rivery?
- Getting started with Estuary Flow is quick and easy. Sign up for a free account and start building your first pipeline in minutes.
- Explore the Getting Started docs to learn how to capture, transform, and materialize data.
- Join the Slack community to ask questions and get real-time help.
- Watch the Estuary 101 On-Demand Webinar for a complete walkthrough.
- Have questions? Contact us — we’re happy to help!
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