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support

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Description

PySpark serves as the Python interface for Apache Spark, enabling the development of Spark applications through Python APIs and offering an interactive shell for data analysis in a distributed setting. In addition to facilitating Python-based development, PySpark encompasses a wide range of Spark functionalities, including Spark SQL, DataFrame support, Streaming capabilities, MLlib for machine learning, and the core features of Spark itself. Spark SQL, a dedicated module within Spark, specializes in structured data processing and introduces a programming abstraction known as DataFrame, functioning also as a distributed SQL query engine. Leveraging the capabilities of Spark, the streaming component allows for the execution of advanced interactive and analytical applications that can process both real-time and historical data, while maintaining the inherent advantages of Spark, such as user-friendliness and robust fault tolerance. Furthermore, PySpark's integration with these features empowers users to handle complex data operations efficiently across various datasets.

Description

VeloDB, which utilizes Apache Doris, represents a cutting-edge data warehouse designed for rapid analytics on large-scale real-time data. It features both push-based micro-batch and pull-based streaming data ingestion that occurs in mere seconds, alongside a storage engine capable of real-time upserts, appends, and pre-aggregations. The platform delivers exceptional performance for real-time data serving and allows for dynamic interactive ad-hoc queries. VeloDB accommodates not only structured data but also semi-structured formats, supporting both real-time analytics and batch processing capabilities. Moreover, it functions as a federated query engine, enabling seamless access to external data lakes and databases in addition to internal data. The system is designed for distribution, ensuring linear scalability. Users can deploy it on-premises or as a cloud service, allowing for adaptable resource allocation based on workload demands, whether through separation or integration of storage and compute resources. Leveraging the strengths of open-source Apache Doris, VeloDB supports the MySQL protocol and various functions, allowing for straightforward integration with a wide range of data tools, ensuring flexibility and compatibility across different environments.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Apache Spark Yes 
Amazon SageMaker Data Wrangler Yes 
Apache Doris No 
Apache Flink No 
Apache Kafka No 
Comet LLM Yes 
Feast Yes 
Fosfor Decision Cloud Yes 
MySQL No 
Tecton Yes 
Union Pandera Yes 
dbt No 

Integrations

Apache Spark Yes 
Amazon SageMaker Data Wrangler No 
Apache Doris Yes 
Apache Flink Yes 
Apache Kafka Yes 
Comet LLM No 
Feast No 
Fosfor Decision Cloud No 
MySQL Yes 
Tecton No 
Union Pandera No 
dbt Yes 

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

PySpark

Website

spark.apache.org/docs/latest/api/python/

Vendor Details

Company Name

VeloDB

Founded

2023

Country

Singapore

Website

www.velodb.io

Product Features

Application Development

Access Controls/Permissions No 
Code Assistance No 
Code Refactoring No 
Collaboration Tools No 
Compatibility Testing No 
Data Modeling No 
Debugging No 
Deployment Management No 
Graphical User Interface No 
Mobile Development No 
No-Code No 
Reporting/Analytics No 
Software Development No 
Source Control No 
Testing Management No 
Version Control No 
Web App Development No 

Product Features

Data Warehouse

Ad hoc Query No 
Analytics No 
Data Integration No 
Data Migration No 
Data Quality Control No 
ETL - Extract / Transfer / Load No 
In-Memory Processing No 
Match & Merge No 

Alternatives

Alternatives

Apache Doris Reviews

Apache Doris

The Apache Software Foundation
Apache Spark Reviews

Apache Spark

Apache Software Foundation
Spark Streaming Reviews

Spark Streaming

Apache Software Foundation