Offering

Streaming to Lakehouse

Enabling seamless stream-to-Lakehouse pipelines without custom ETL

Transform Kafka streams into analytics-ready data without complex pipelines

Many organizations rely on Kafka for real-time event streaming, powering transactions, IoT device outputs, and customer interactions. However, turning raw Kafka streams into queryable tables suitable for analytics remains complex, fragile, and costly. Traditional ETL pipelines require custom transformations, schema handling, and compaction logic that slow down time-to-insight and increase operational overhead.

Data Reply addresses this challenge by helping organizations effectively adopt solutions such as Confluent’s Tableflow. With Tableflow, Kafka topics are continuously and fully automatically materialized into open table formats like Apache Iceberg or Delta Lake. This enables analytics and machine learning systems to query streaming data directly, without the need for custom ETL pipelines. It provides a unified, consistent view of data across operational and analytical systems, helping companies fully leverage event data while minimizing costs and engineering complexity.

What sets our offer apart

With our Streaming-to-Lakehouse Offering, we bring together Confluent’s technology and our consulting expertise to deliver scalable, secure, and future-proof data architectures. We support clients end-to-end in: 

Streaming architecture

Designing and implementing architectures that use Confluent Tableflow to continuously materialize Kafka streams into analytics-ready Iceberg or Delta tables

Unified governance

Implementing external catalog integration (e.g., AWS Glue, Apache Polaris, Snowflake Open Catalog, and Unity Catalog) 

Flexible Storage

Integrating your own Amazon S3 bucket as a storage solution, or leveraging Confluent’s managed storage offering

Cost Efficiency

Ensuring cost-efficient and scalable storage and query performance

Secure by Design

Integrating governance, security, and compliance practices throughout the pipeline 

The technology behind your success

Streaming-to-Table Pipelines

We use Tableflow to convert Kafka events into queryable tables, automating ingestion, transformation, and catalog registration. Data can be stored in your S3 bucket or Confluent’s managed storage.

Schema Evolution & Data Quality

With Tableflow, schema changes such as adding fields or widening types are managed automatically, keeping downstream tables consistent and accessible.

Maintenance and Metadata Management

Automatic file compaction reduces small-file issues, while snapshot and version expiration are also handled automatically. The combination leads to improved performance and lower infrastructure costs.

Integration into Existing Ecosystems

Tableflow tables are seamlessly accessible from data lakes and warehouses like Athena, Databricks, or Snowflake via native integrations and the Iceberg REST Catalog.

With our Streaming-to-Lakehouse offering,
organizations benefit from:

Data Reply combines deep expertise in streaming architectures, open data formats, and modern cloud ecosystems with strategic consulting to deliver impactful solutions. Our consultants are experienced in designing, implementing, and operating event-driven data platforms that scale.

By leveraging Confluent Tableflow as part of our broader streaming and analytics portfolio, we empower organizations to move from raw Kafka events to actionable insights quickly and securely. With Data Reply, clients gain not only the technology but also the guidance, best practices, and governance frameworks to ensure long-term success.

Data Reply

As part of the Reply group, Data Reply offers a wide range of services that support customers in becoming data driven. We operate in various industries and business areas and work intensively with our customers so that they can achieve meaningful results through the effective use of data. Data Reply offers many years of experience in transformation projects to achieve “data-driven companies”. We focus on the development of data platforms, machine learning solutions and streaming applications - automated, efficient, and scalable - without making any compromises in IT security.