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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Oracle Big Data Service simplifies the deployment of Hadoop clusters for customers, offering a range of VM configurations from 1 OCPU up to dedicated bare metal setups. Users can select between high-performance NVMe storage or more budget-friendly block storage options, and have the flexibility to adjust the size of their clusters as needed. They can swiftly establish Hadoop-based data lakes that either complement or enhance existing data warehouses, ensuring that all data is both easily accessible and efficiently managed. Additionally, the platform allows for querying, visualizing, and transforming data, enabling data scientists to develop machine learning models through an integrated notebook that supports R, Python, and SQL. Furthermore, this service provides the capability to transition customer-managed Hadoop clusters into a fully-managed cloud solution, which lowers management expenses and optimizes resource use, ultimately streamlining operations for organizations of all sizes. By doing so, businesses can focus more on deriving insights from their data rather than on the complexities of cluster management.

Description

lakeFS allows you to control your data lake similarly to how you manage your source code, facilitating parallel pipelines for experimentation as well as continuous integration and deployment for your data. This platform streamlines the workflows of engineers, data scientists, and analysts who are driving innovation through data. As an open-source solution, lakeFS enhances the resilience and manageability of object-storage-based data lakes. With lakeFS, you can execute reliable, atomic, and versioned operations on your data lake, encompassing everything from intricate ETL processes to advanced data science and analytics tasks. It is compatible with major cloud storage options, including AWS S3, Azure Blob Storage, and Google Cloud Storage (GCS). Furthermore, lakeFS seamlessly integrates with a variety of modern data frameworks such as Spark, Hive, AWS Athena, and Presto, thanks to its API compatibility with S3. The platform features a Git-like model for branching and committing that can efficiently scale to handle exabytes of data while leveraging the storage capabilities of S3, GCS, or Azure Blob. In addition, lakeFS empowers teams to collaborate more effectively by allowing multiple users to work on the same dataset without conflicts, making it an invaluable tool for data-driven organizations.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Hadoop
Amazon Athena
Amazon Kinesis
Amazon S3
Amazon SES
Amazon Web Services (AWS)
Apache Airflow
Apache Flink
Apache Hive
Apache Kafka
Apache Spark
Astro by Astronomer
Azure Blob Storage
Databricks
Delta Lake
Jupyter Notebook
Looker
MLflow
Oracle Cloud Infrastructure
Presto

Integrations

Hadoop
Amazon Athena
Amazon Kinesis
Amazon S3
Amazon SES
Amazon Web Services (AWS)
Apache Airflow
Apache Flink
Apache Hive
Apache Kafka
Apache Spark
Astro by Astronomer
Azure Blob Storage
Databricks
Delta Lake
Jupyter Notebook
Looker
MLflow
Oracle Cloud Infrastructure
Presto

Pricing Details

$0.1344 per hour
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Oracle

Founded

1977

Country

United States

Website

www.oracle.com/big-data/big-data-service/

Vendor Details

Company Name

Treeverse

Founded

2020

Country

Israel

Website

lakefs.io

Product Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Product Features

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

Alternatives

Alternatives

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