Fast, Low Cost, and Infinitely Scalable Data Ingestion

Change Data Capture, Event Streaming, and Cloud Storage: Seamlessly Configure and Manage Data Ingestion for Near Real-Time Replication and Transfer

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Accelerate data ingestion with an easy-to-configure and fully-managed solution

Change Data Capture (CDC)

Continuously replicate data from operational databases (including PostgreSQL, MySQL, MongoDB, SQL Server, and more) to the data lakehouse in near real-time.

Event Streaming

Efficiently ingest high-volume Kafka streams (click streams, IoT devices, transaction logs, and more) from Confluent Cloud and Amazon MSK.

Cloud Storage

Automatically transfer data in multiple formats (Avro, JSON, CSV, ORC, Parquet, XML) from cloud storage (e.g., Amazon S3, Google Cloud Storage) into the data lakehouse.

Advanced Tools for Fast & Cost-Effective Data Ingestion

Enhance Data Quality

  • Eliminate Data Duplication: The original read-write data lakehouse delivers database-like features, including ACID transactions and schema evolution, to create a single, reliable repository for all data use cases.
  • Refresh Outdated Data: Leverage incremental processing and low-latency ingestion to easily handle data warehouse-style workloads, such as BI and reporting, on low-cost cloud storage.
  • Leverage Mutable Tables: Seamlessly replicate business application sources to your data lakehouse for unified data views and integrated analytics while adhering to regulatory requirements such as GDPR.

Streamline Data Integration

  • Integrate Disparate Systems: Integrate separate batch and streaming pipelines into a single, unified workflow accessing hundreds of data sources through pre-built, open-source, and partner connectors.
  • Break Down Data Silos: Consolidate workloads around one data lakehouse environment with comprehensive support for all applications, from business intelligence to data science.
  • Simplify Data Management: Eliminate the need for specialized skills with automated lakehouse provisioning and tuning.

Master Data Volume, Velocity, & Costs

  • Scale with Ease: Harness the data lake's rapid ingestion for high-velocity writes and the data warehouse's flexibility and speed for advanced updates, deletions, and fast querying.
  • Achieve Near Real-time Insights: Ingest and store data as it arrives for near real-time data availability without relying on batch processing.
  • Reduce Costs: Optimize expenses by leveraging native cloud services and low-cost cloud storage.

Streamlined Data Ingestion with Onehouse

Continuously replicate data in near-real time, manage high-volume event streams, and transfer files across various sources, while enjoying the flexibility and affordability of the Universal Data Lakehouse architecture.

Key Features to Maximize Your Snowflake Environment

Built on Apache Hudi

Leverage Apache Hudi for efficient data management with upsert, delete, and time travel features for cost-effective storage and faster processing in the cloud.

End-to-End Change Data Capture (CDC)

Configure comprehensive CDC pipelines to ensure accurate and up-to-date data replication for analysis.

Continuous Data Ingestion

Implement low-latency, continuous ingestion of data and support checkpointing and schema evolution for robust streaming data pipelines.

Automatic Performance Tuning

Optimize data operations automatically to reduce manual tuning and maintenance, and ensure top-notch performance.

Interoperability with Apache XTable

Expose Hudi-ingested tables as Iceberg or Delta Lake tables without copying or moving data for tool and query engine flexibility.

Managed Infrastructure

Rely on Onehouse for a fully automated, secure, managed data lake infrastructure in your VPC.

Universal Data Lakehouse Success

Learn how Apna improved their data freshness from several hours to just a few minutes.

apna’s journey


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Learn How to Accelerate Data Ingestion


Synchronize PostgreSQL and your Lakehouse: CDC with Onehouse on AWS
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Database Replication Into The Lakehouse With Onehouse's Confluent CDC Source
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Ingest PostgreSQL CDC Data Into The Data Lakehouse Using Onehouse
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Streaming Ingestion At Scale: Kafka To The Lakehouse
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CDC Postgres Demo
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Accelerate Data Ingestion with Onehouse.

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