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
Introducing a robust cross-platform columnar database designed for high-performance historical time-series data, which includes:
- A compute engine optimized for in-memory operations
- A streaming processor that functions in real time
- A powerful query and programming language known as q
Kdb+ drives the kdb Insights portfolio and KDB.AI, offering advanced time-focused data analysis and generative AI functionalities to many of the world's top enterprises. Recognized for its unparalleled speed, kdb+ has been independently benchmarked* as the leading in-memory columnar analytics database, providing exceptional benefits for organizations confronting complex data challenges. This innovative solution significantly enhances decision-making capabilities, enabling businesses to adeptly respond to the ever-evolving data landscape. By leveraging kdb+, companies can gain deeper insights that lead to more informed strategies.
API Access
Has API
No
API Access
Has API
No
Integrations
QStudio
Yes
APERIO DataWise
Yes
Apache DataFusion
Yes
Blotout
Yes
Data Sentinel
Yes
Gravity Data
Yes
Hadoop
Yes
Indexima Data Hub
Yes
MLJAR Studio
Yes
Mage Platform
Yes
Integrations
QStudio
Yes
APERIO DataWise
No
Apache DataFusion
No
Blotout
No
Data Sentinel
No
Gravity Data
No
Hadoop
No
Indexima Data Hub
No
MLJAR Studio
No
Mage Platform
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)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
No
Webinars
No
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
KX Systems
Founded
1993
Country
United Kingdom
Website
kx.com/products/kdb/