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features
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support

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Description

Parquet was developed to provide the benefits of efficient, compressed columnar data representation to all projects within the Hadoop ecosystem. Designed with a focus on accommodating complex nested data structures, Parquet employs the record shredding and assembly technique outlined in the Dremel paper, which we consider to be a more effective strategy than merely flattening nested namespaces. This format supports highly efficient compression and encoding methods, and various projects have shown the significant performance improvements that arise from utilizing appropriate compression and encoding strategies for their datasets. Furthermore, Parquet enables the specification of compression schemes at the column level, ensuring its adaptability for future developments in encoding technologies. It is crafted to be accessible for any user, as the Hadoop ecosystem comprises a diverse range of data processing frameworks, and we aim to remain neutral in our support for these different initiatives. Ultimately, our goal is to empower users with a flexible and robust tool that enhances their data management capabilities across various applications.

Description

Oracle Big Data Discovery is an impressively visual and user-friendly tool that harnesses the capabilities of Hadoop to swiftly convert unrefined data into actionable business insights in just minutes, eliminating the necessity for mastering complicated software or depending solely on highly trained individuals. This product enables users to effortlessly locate pertinent data sets within Hadoop, investigate the data to grasp its potential quickly, enhance and refine data for improved quality, analyze the information for fresh insights, and disseminate findings back to Hadoop for enterprise-wide utilization. By implementing BDD as the hub of your data laboratory, your organization can create a cohesive environment that facilitates the exploration of all data sources in Hadoop and the development of projects and BDD applications. Unlike conventional analytics tools, BDD allows a broader range of individuals to engage with big data, significantly reducing the time spent on loading and updating data, thereby allowing a greater focus on the actual analysis of substantial data sets. This shift not only streamlines workflows but also empowers teams to derive insights more efficiently and collaboratively.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Hadoop Yes 
Arroyo Yes 
Astera Dataprep Yes 
Fortinet SD-WAN No 
Gravity Data Yes 
IBM Db2 Event Store Yes 
MLJAR Studio Yes 
QuerySurge Yes 
SAS Studio Yes 
Scoop Analytics No 
StarfishETL Yes 
Tad Yes 
Tenzir Yes 
Timeplus Yes 
Tonic Ephemeral Yes 
VMware Tanzu CloudHealth No 
Warp 10 Yes 
e6data Yes 

Integrations

Hadoop Yes 
Arroyo No 
Astera Dataprep No 
Fortinet SD-WAN Yes 
Gravity Data No 
IBM Db2 Event Store No 
MLJAR Studio No 
QuerySurge No 
SAS Studio No 
Scoop Analytics Yes 
StarfishETL No 
Tad No 
Tenzir No 
Timeplus No 
Tonic Ephemeral No 
VMware Tanzu CloudHealth Yes 
Warp 10 No 
e6data No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
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 Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

The Apache Software Foundation

Founded

1999

Country

United States

Website

parquet.apache.org

Vendor Details

Company Name

Oracle

Founded

1977

Country

United States

Website

www.oracle.com/middleware/technologies/big-data-discovery.html

Product Features

Product Features

Data Discovery

Contextual Search No 
Data Classification No 
Data Matching No 
False Positives Reduction No 
Self Service Data Preparation Yes 
Sensitive Data Identification No 
Visual Analytics Yes 

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Alternatives

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