Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
Hypertable provides a high-performance, scalable database solution that enhances the efficiency of your big data applications while minimizing hardware usage. This platform offers exceptional efficiency and outperforms its competitors, leading to significant cost reductions for users. Its robust and proven architecture supports numerous services at Google. Users can enjoy the advantages of open-source technology backed by a vibrant and active community. With a C++ implementation, Hypertable ensures optimal performance. Additionally, it offers around-the-clock support for critical big data operations. Clients benefit from direct access to the expertise of the core developers behind Hypertable. Specifically engineered to address scalability challenges that traditional relational database management systems struggle with, Hypertable leverages a design model pioneered by Google to effectively tackle scaling issues, making it superior to other NoSQL alternatives available today. Its innovative approach not only resolves current scalability needs but also anticipates future demands in data management.
API Access
Has API
No
API Access
Has API
No
Integrations
Hadoop
Yes
Amazon SageMaker Data Wrangler
Yes
Apache DataFusion
Yes
Astera Dataprep
Yes
Autymate
Yes
Blotout
Yes
GribStream
Yes
Indexima Data Hub
Yes
Mage Platform
Yes
Mage Sensitive Data Discovery
Yes
Integrations
Hadoop
Yes
Amazon SageMaker Data Wrangler
No
Apache DataFusion
No
Astera Dataprep
No
Autymate
No
Blotout
No
GribStream
No
Indexima Data Hub
No
Mage Platform
No
Mage Sensitive Data Discovery
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
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
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
No
Live Training (Online)
No
In Person
Yes
Vendor Details
Company Name
The Apache Software Foundation
Founded
1999
Country
United States
Website
parquet.apache.org
Vendor Details
Company Name
Hypertable
Country
United States
Website
www.hypertable.com
Product Features
Product Features
Big Data
Collaboration
No
Data Blends
No
Data Cleansing
No
Data Mining
No
Data Visualization
No
Data Warehousing
No
High Volume Processing
No
No-Code Sandbox
No
Predictive Analytics
No
Templates
No