Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
OLake Fusion is an application designed for self-hosting that focuses on the management of Apache Iceberg tables within data lakehouses. This tool automates the process of scheduled table compaction, effectively merging smaller data files and transforming delete files to enhance the overall layout of tables as data is consistently added, modified, or removed. Users have the ability to set maintenance schedules at the individual table level, choosing from compaction tiers labeled Lite, Medium, and Full, while also being able to assess table health, file metrics, and monitor maintenance activities and logs via an intuitive web interface. Additionally, Fusion integrates seamlessly with various Iceberg catalogs, such as AWS Glue, Hive Metastore, JDBC, and REST-based catalog systems like Nessie, Polaris, Unity Catalog, and Lakekeeper, allowing it to manage tables that were created externally to OLake. Deployment options include Docker or Kubernetes, making it suitable for a team’s cloud infrastructure or on-premises setup. This tool is particularly beneficial for data engineers and platform teams who are managing analytical lakehouses that utilize Apache Iceberg, ensuring efficient data handling within their environments. The flexibility and robustness of OLake Fusion make it an essential asset for modern data management practices.
Description
A data lakehouse represents a contemporary, open architecture designed for storing, comprehending, and analyzing comprehensive data sets. It merges the robust capabilities of traditional data warehouses with the extensive flexibility offered by widely used open-source data technologies available today. Constructing a data lakehouse can be accomplished on Oracle Cloud Infrastructure (OCI), allowing seamless integration with cutting-edge AI frameworks and pre-configured AI services such as Oracle’s language processing capabilities. With Data Flow, a serverless Spark service, users can concentrate on their Spark workloads without needing to manage underlying infrastructure. Many Oracle clients aim to develop sophisticated analytics powered by machine learning, applied to their Oracle SaaS data or other SaaS data sources. Furthermore, our user-friendly data integration connectors streamline the process of establishing a lakehouse, facilitating thorough analysis of all data in conjunction with your SaaS data and significantly accelerating the time to achieve solutions. This innovative approach not only optimizes data management but also enhances analytical capabilities for businesses looking to leverage their data effectively.
API Access
Has API
No
API Access
Has API
No
Integrations
AWS Glue
Yes
Apache Hive
Yes
Apache Iceberg
Yes
NLSQL
No
OLake Go
Yes
Unity Catalog
Yes
Integrations
AWS Glue
No
Apache Hive
No
Apache Iceberg
No
NLSQL
Yes
OLake Go
No
Unity Catalog
No
Pricing Details
$0
The open-source software has no license charge; customers pay for the compute and storage they provision.
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Datazip
Country
United States
Website
olake.io/olake-fusion/
Vendor Details
Company Name
Oracle
Founded
1977
Country
United States
Website
www.oracle.com/data-lakehouse/
Product Features
Product Features
Data Management
Customer Data
No
Data Analysis
No
Data Capture
No
Data Integration
No
Data Migration
No
Data Quality Control
No
Data Security
No
Information Governance
No
Master Data Management
No
Match & Merge
No
Data Warehouse
Ad hoc Query
No
Analytics
No
Data Integration
No
Data Migration
No
Data Quality Control
No
ETL - Extract / Transfer / Load
No
In-Memory Processing
No
Match & Merge
No