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What is OLake Fusion?

OLake Fusion is an innovative self-hosted application aimed at effectively managing Apache Iceberg tables within data lakehouses. This application streamlines the scheduled table compaction process, allowing for the merging of smaller data files and the transformation of delete files to improve table organization as data is continuously added, altered, or removed. Users can customize maintenance schedules for each table, selecting from compaction options categorized as Lite, Medium, or Full, and can also evaluate table health, file metrics, and track maintenance logs through a user-friendly web interface. Furthermore, Fusion boasts seamless integration with various Iceberg catalogs, including AWS Glue, Hive Metastore, JDBC, and REST-based systems like Nessie, Polaris, Unity Catalog, and Lakekeeper, enabling it to manage tables originally created outside the OLake framework. Deployment is versatile, offering options for Docker or Kubernetes, making it adaptable for either cloud infrastructure or on-premises environments. This tool proves especially advantageous for data engineers and platform teams overseeing analytical lakehouses that leverage Apache Iceberg, facilitating efficient data management practices. With its combination of flexibility and robustness, OLake Fusion stands out as a crucial resource for contemporary data management strategies, ultimately driving better performance and organization of data workflows.

What is Google Cloud Lakehouse?

Google Cloud Lakehouse is an advanced data platform that unifies data warehouses and data lakes into a single, integrated storage and analytics solution. It enables organizations to work with open data formats such as Apache Iceberg, Parquet, and ORC, ensuring flexibility and interoperability across systems. By allowing access to a single copy of data, it eliminates the need for duplication and complex data pipelines. The platform includes a centralized runtime catalog for managing metadata, resources, and access controls efficiently. It provides fine-grained security through IAM roles and table-level permissions, ensuring strong governance and compliance. Google Cloud Lakehouse supports scalable data processing and integrates with tools like Apache Spark for advanced analytics and machine learning workflows. It is designed to handle large volumes of data while maintaining performance and reliability. The platform includes features for replication and disaster recovery, helping ensure data availability and resilience. Comprehensive documentation, guides, and training resources make it easier for teams to get started and optimize their workflows. It also simplifies the management of Iceberg tables and other data structures. The system supports modern data architectures, enabling seamless integration with other Google Cloud services. By unifying storage and analytics, it reduces operational complexity and improves efficiency. Overall, Google Cloud Lakehouse empowers organizations to manage, analyze, and scale their data more effectively in a single platform.

Media

Media

Integrations Supported

Apache Iceberg
AWS Glue
Apache Hive
OLake Go
Unity Catalog

Integrations Supported

Apache Iceberg
Amazon S3
Apache Spark
Azure Data Lake
Google Cloud BigQuery
Google Cloud Storage
Presto

API Availability

API Availability

Has API

Pricing Information

$0
The open-source software has no license charge; customers pay for the compute and storage they provision.
Free Version

Pricing Information

$5 per TB
Free Trial Offered?

Supported Platforms

On-Prem

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
On-Site Training

Company Facts

Organization Name

Datazip

Company Location

United States

Company Website

olake.io/olake-fusion/

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

docs.cloud.google.com/lakehouse/docs

Categories and Features

Data Lake

Not specified

Categories and Features

Data Lake

Not specified

Data Warehouse

Not specified

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No Alternatives

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