Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Google Cloud BigQuery Reviews & Ratings
    4.5 out of 5 stars 2,027 Ratings
    Company Website for Google Cloud BigQuery
  • TinyPNG Reviews & Ratings
    4.7 out of 5 stars 72 Ratings
    Company Website for TinyPNG
  • Bacula Enterprise Reviews & Ratings
    4.5 out of 5 stars 125 Ratings
    Company Website for Bacula Enterprise
  • PDF Guru Reviews & Ratings
    4.3 out of 5 stars 101,418 Ratings
    Company Website for PDF Guru
  • CirrusPrint Reviews & Ratings
    5.0 out of 5 stars 2 Ratings
    Company Website for CirrusPrint
  • Comet Backup Reviews & Ratings
    4.5 out of 5 stars 219 Ratings
    Company Website for Comet Backup
  • MobiPDF Reviews & Ratings
    4.6 out of 5 stars 8,085 Ratings
    Company Website for MobiPDF
  • 3Q Reviews & Ratings
    4.9 out of 5 stars 14 Ratings
    Company Website for 3Q
  • Google Cloud Platform Reviews & Ratings
    4.5 out of 5 stars 61,066 Ratings
    Company Website for Google Cloud Platform
  • Kitecyber Reviews & Ratings
    4.9 out of 5 stars 87 Ratings
    Company Website for Kitecyber

What is Apache Parquet?

Parquet was created to offer the advantages of efficient and compressed columnar data formats across all initiatives within the Hadoop ecosystem. It takes into account complex nested data structures and utilizes the record shredding and assembly method described in the Dremel paper, which we consider to be a superior approach compared to just flattening nested namespaces. This format is specifically designed for maximum compression and encoding efficiency, with numerous projects demonstrating the substantial performance gains that can result from the effective use of these strategies. Parquet allows users to specify compression methods at the individual column level and is built to accommodate new encoding technologies as they arise and become accessible. Additionally, Parquet is crafted for widespread applicability, welcoming a broad spectrum of data processing frameworks within the Hadoop ecosystem without showing bias toward any particular one. By fostering interoperability and versatility, Parquet seeks to enable all users to fully harness its capabilities, enhancing their data processing tasks in various contexts. Ultimately, this commitment to inclusivity ensures that Parquet remains a valuable asset for a multitude of data-centric applications.

What is Actian Analytics Engine?

Actian Analytics Engine is an advanced analytics database platform built to deliver high-speed data processing and real-time insights for enterprise applications. It features a columnar, in-memory architecture that enables efficient storage and rapid query execution. The platform uses distributed processing and parallel query execution to analyze massive datasets with ease. Vectorized processing and CPU cache optimization significantly improve performance, allowing faster data retrieval and analysis. Actian Analytics Engine supports data ingestion from various sources, including structured and unstructured data formats. It provides real-time updates without performance degradation, ensuring that users always work with the latest information. The platform is capable of handling complex analytical workloads across multiple industries and use cases. It includes enterprise-grade security features such as encryption at rest and in transit, along with dynamic data masking. Flexible deployment options allow organizations to run the platform on-premises or in cloud environments like AWS, Azure, and Google Cloud. The system is designed for simplicity, requiring minimal setup and reducing the need for manual tuning. Advanced features like automatic indexing and partitioning improve query performance and resource management. Actian Analytics Engine enables organizations to scale their analytics capabilities while maintaining efficiency. By combining performance, scalability, and security, it helps businesses make faster and more informed decisions.

Media

Media

Integrations Supported

Semarchy xDI
APERIO DataWise
Amazon SageMaker Data Wrangler
Ficstar
Flyte
Mage Platform
Meltano
OrcaSheets
Querri
SAS Studio
SDF
SSIS Integration Toolkit
Sliq
StarfishETL
Tad
Tictable
Tonic Ephemeral
Visplore
e6data

Integrations Supported

Semarchy xDI
Zoho DataPrep

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

Windows
Mac
Linux

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
Webinars

Training Options

Documentation Hub

Company Facts

Organization Name

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

parquet.apache.org

Company Facts

Organization Name

Actian

Date Founded

2005

Company Location

United States

Company Website

www.actian.com/databases/analytics-engine/

Categories and Features

Columnar Databases

Not specified

Categories and Features

Big Data

Not specified

Columnar Databases

Not specified

Popular Alternatives

Apache Iceberg Reviews & Ratings

Apache Iceberg

Apache Software Foundation

Popular Alternatives

kdb+ Reviews & Ratings

kdb+

KX Systems
CelerData Cloud Reviews & Ratings

CelerData Cloud

CelerData