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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

Upsolver makes it easy to create a governed data lake, manage, integrate, and prepare streaming data for analysis. Only use auto-generated schema on-read SQL to create pipelines. A visual IDE that makes it easy to build pipelines. Add Upserts to data lake tables. Mix streaming and large-scale batch data. Automated schema evolution and reprocessing of previous state. Automated orchestration of pipelines (no Dags). Fully-managed execution at scale Strong consistency guarantee over object storage Nearly zero maintenance overhead for analytics-ready information. Integral hygiene for data lake tables, including columnar formats, partitioning and compaction, as well as vacuuming. Low cost, 100,000 events per second (billions every day) Continuous lock-free compaction to eliminate the "small file" problem. Parquet-based tables are ideal for quick queries.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

PuppyGraph Yes 
APERIO DataWise Yes 
Amazon SageMaker Data Wrangler Yes 
Astera Dataprep Yes 
CSViewer Yes 
Eco No 
Ficstar Yes 
Gravity Data Yes 
GribStream Yes 
Hadoop Yes 
Hive No 
Indexima Data Hub Yes 
Mage Platform Yes 
OpenObserve Yes 
PI.EXCHANGE Yes 
QuerySurge Yes 
SDF Yes 
Tenzir Yes 
Tictable Yes 
Timbr.ai Yes 

Integrations

PuppyGraph Yes 
APERIO DataWise No 
Amazon SageMaker Data Wrangler No 
Astera Dataprep No 
CSViewer No 
Eco Yes 
Ficstar No 
Gravity Data No 
GribStream No 
Hadoop No 
Hive Yes 
Indexima Data Hub No 
Mage Platform No 
OpenObserve No 
PI.EXCHANGE No 
QuerySurge No 
SDF No 
Tenzir No 
Tictable No 
Timbr.ai No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version Yes 

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

Vendor Details

Company Name

The Apache Software Foundation

Founded

1999

Country

United States

Website

parquet.apache.org

Vendor Details

Company Name

Upsolver

Founded

2014

Country

Israel

Website

www.upsolver.com

Product Features

Product Features

Big Data

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

Data Mining

Data Extraction No 
Data Visualization No 
Fraud Detection No 
Linked Data Management No 
Machine Learning No 
Predictive Modeling No 
Semantic Search No 
Statistical Analysis No 
Text Mining No 

Data Preparation

Collaboration Tools No 
Data Access No 
Data Blending No 
Data Cleansing No 
Data Governance No 
Data Mashup No 
Data Modeling No 
Data Transformation No 
Machine Learning No 
Visual User Interface No 

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