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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 Apache Iceberg?

Iceberg is an advanced format tailored for high-performance large-scale analytics, merging the user-friendly nature of SQL tables with the robust demands of big data. It allows multiple engines, including Spark, Trino, Flink, Presto, Hive, and Impala, to access the same tables seamlessly, enhancing collaboration and efficiency. Users can execute a variety of SQL commands to incorporate new data, alter existing records, and perform selective deletions. Moreover, Iceberg has the capability to proactively optimize data files to boost read performance, or it can leverage delete deltas for faster updates. By expertly managing the often intricate and error-prone generation of partition values within tables, Iceberg minimizes unnecessary partitions and files, simplifying the query process. This optimization leads to a reduction in additional filtering, resulting in swifter query responses, while the table structure can be adjusted in real time to accommodate evolving data and query needs, ensuring peak performance and adaptability. Additionally, Iceberg’s architecture encourages effective data management practices that are responsive to shifting workloads, underscoring its significance for data engineers and analysts in a rapidly changing environment. This makes Iceberg not just a tool, but a critical asset in modern data processing strategies.

Media

Media

Integrations Supported

Apache Hive
OLake Go
AWS Glue
Apache Iceberg
Unity Catalog

Integrations Supported

Apache Hive
OLake Go
Actian Data Observability
Amazon Data Firehose
Apache Flink
Apache Spark
Cazpian
CelerData Cloud
CodeConductor
Dremio
OLake Fusion
Onehouse
R2 SQL
SQL
Salesforce Data 360
StarRocks
Trino

API Availability

API Availability

Pricing Information

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

Pricing Information

Free
Open source
Free Version

Supported Platforms

On-Prem

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Datazip

Company Location

United States

Company Website

olake.io/olake-fusion/

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

iceberg.apache.org

Categories and Features

Data Lake

Not specified

Categories and Features

Big Data

Not specified

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