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7 Best Tools to Stream & Ingest Data into Apache Iceberg (2025)

Discover 7 powerful tools to stream and ingest data into Apache Iceberg. Build real-time, scalable pipelines for your data lakehouse with ease.

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TL;DR

Apache Iceberg is an advanced open table format that enables efficient data storage and analytics at scale. This article highlights 7 essential tools for streaming and ingesting data into Iceberg, ensuring real-time insights and reliable data pipelines


Streaming Data into Apache Iceberg: Tools for a Scalable Data Lakehouse

Apache Iceberg has transformed how organizations handle large-scale data, offering features like ACID transactions, schema evolution, and time travel. It allows businesses to build robust data lakehouses that unify structured and unstructured data for analytics and machine learning.

To fully leverage Iceberg’s capabilities, efficient data ingestion and streaming are crucial. Whether it’s real-time streaming, batch processing, or change data capture (CDC), choosing the right ingestion tool can ensure data consistency, performance, and ease of use.

This article explores 7 top tools for streaming and ingesting data into Apache Iceberg. From real-time data integration platforms to scalable batch processing engines, these solutions cater to a range of use cases and organizational needs, making it easier to harness the full power of your data lakehouse.

7 Best Tools to Stream and Ingest Data into Apache Iceberg

Building an efficient, scalable Iceberg-based data lakehouse starts with choosing the right pipeline tools. Here are 7 solutions that help make real-time streaming and ingestion to Iceberg faster and more reliable:

1. Estuary Flow

Ingest Data into Apache Iceberg With Estuary Flow

Stream and Ingest Real-Time Data into Apache Iceberg With Estuary Flow

Estuary Flow is a real-time data integration platform designed to simplify the process of building and managing data pipelines. It enables organizations to efficiently collect, process, and deliver data across various systems and applications. Estuary Flow supports data integration with Apache Iceberg, making it easier to ingest and organize data into Iceberg tables, ensuring compatibility with modern data lakehouse architectures.

Key Features:

  • Real-Time Data Ingestion: Estuary Flow allows for the continuous collection of data from multiple sources, ensuring that information is always up-to-date.
  • Change Data Capture (CDC): The platform supports CDC, enabling the detection and capture of data changes in real-time, which is crucial for maintaining data consistency across systems.
  • Schema Evolution: Estuary Flow manages changes in data schemas automatically, allowing for flexibility as data structures evolve over time.
  • Scalability: Built to handle large volumes of data, Estuary Flow scales seamlessly to accommodate growing data needs without compromising performance.
  • Integration with Apache Iceberg: Estuary integrates with Apache Iceberg, facilitating efficient data storage and analytics within a data lakehouse architecture.

Related Articles on Using Estuary Flow to Ingest Data into Apache Iceberg:

2. Dremio

Dremio is a data lakehouse platform that simplifies data management and analytics. It offers an enterprise data catalog for Apache Iceberg, providing features like data versioning and governance. Dremio's SQL query engine delivers high-performance queries, and its unified analytics support self-service across various data sources.

3. Apache Spark

Apache Spark is a unified analytics engine for large-scale data processing. It integrates with Apache Iceberg, allowing users to perform batch and streaming data processing with ease. Spark's DataFrame API enables complex transformations and actions on Iceberg tables, supporting operations like reading, writing, and managing table metadata. 

Apache Flink is a framework and distributed processing engine for stateful computations over data streams. It integrates with Apache Iceberg to provide real-time data ingestion and processing capabilities. Flink's support for event-time processing and exactly-once state consistency ensures accurate and reliable data pipelines when working with Iceberg tables.

5. Kafka Connect

Kafka Connect is a framework for connecting Apache Kafka with external systems, including databases and data lakes. It facilitates the ingestion of streaming data into Apache Iceberg tables by capturing real-time data changes and delivering them to Iceberg-managed storage. This integration supports building robust, real-time analytics pipelines. 

6. Upsolver

Upsolver is a cloud-native data integration platform designed for high-scale workloads. It simplifies the ingestion and transformation of streaming data into Apache Iceberg tables. In January 2025, Upsolver was acquired by Qlik, a global leader in data integration, data quality, analytics, and AI. This acquisition enhances Qlik's ability to provide real-time data streaming and Iceberg optimization solutions.

7. Fivetran

Fivetran is an automated data movement platform that offers connectors to various data sources, enabling seamless data replication into destinations like Apache Iceberg. It ensures data consistency and reliability by providing fully managed pipelines that adapt to schema changes and support real-time data synchronization.

Conclusion

Streaming and ingesting data into Apache Iceberg is a critical step in building an efficient and scalable data lakehouse. Among the tools available, each offers unique features to cater to various data ingestion needs, from real-time streaming to batch processing and schema evolution.

While platforms like Apache Spark, Kafka Connect, and Fivetran offer strong ingestion capabilities, Estuary Flow’s real-time streaming focus, flexible schema handling, and built-in CDC support make it stand out. It's a powerful solution for teams looking to simplify real-time data delivery into Apache Iceberg.

Take control of your data pipelines today! Register for Estuary Flow and start free. Experience real-time data integration with Apache Iceberg, designed to fit your needs effortlessly.

FAQs

1. What is Apache Iceberg, and why is it important?

Apache Iceberg is an open table format designed for large-scale data storage and analytics. It supports features like ACID transactions, schema evolution, and time travel, making it ideal for building modern data lakehouses. Iceberg helps organizations unify structured and unstructured data, ensuring consistent, scalable, and high-performing analytics.

2. How do I choose the right tool to stream data into Apache Iceberg?

Estuary Flow is ideal for real-time data streaming into Iceberg. It offers CDC, scalability, and schema handling, ensuring smooth data flows without complex configuration.

3. Can I integrate real-time data streams into Apache Iceberg?

Yes! Tools like Kafka Connect and Estuary Flow are built for streaming real-time updates to Iceberg tables, keeping them always in sync with minimal latency.

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About the author

Picture of Dani Pálma
Dani PálmaHead of Data Engineering Marketing

Dani is a data professional with a rich background in data engineering and real-time data platforms. At Estuary, Daniel focuses on promoting cutting-edge streaming solutions, helping to bridge the gap between technical innovation and developer adoption. With deep expertise in cloud-native and streaming technologies, Dani has successfully supported startups and enterprises in building robust data solutions.

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