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features
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support

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Description

Apache DataFusion is a versatile and efficient query engine crafted in Rust, leveraging Apache Arrow for its in-memory data representation. It caters to developers engaged in creating data-focused systems, including databases, data frames, machine learning models, and real-time streaming applications. With its SQL and DataFrame APIs, DataFusion features a vectorized, multi-threaded execution engine that processes data streams efficiently and supports various partitioned data sources. It is compatible with several native formats such as CSV, Parquet, JSON, and Avro, and facilitates smooth integration with popular object storage solutions like AWS S3, Azure Blob Storage, and Google Cloud Storage. The architecture includes a robust query planner and an advanced optimizer that boasts capabilities such as expression coercion, simplification, and optimizations that consider distribution and sorting, along with automatic reordering of joins. Furthermore, DataFusion allows for extensive customization, enabling developers to incorporate user-defined scalar, aggregate, and window functions along with custom data sources and query languages, making it a powerful tool for diverse data processing needs. This adaptability ensures that developers can tailor the engine to fit their unique use cases effectively.

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.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

SDF Yes 
3LC No 
Amazon Data Firehose No 
Amazon SageMaker Data Wrangler No 
Apache Arrow Yes 
Arroyo No 
Blotout No 
CSViewer No 
Google Cloud Storage Yes 
GribStream No 
IBM Db2 Event Store No 
MLJAR Studio No 
OpenObserve No 
OrcaSheets No 
QuerySurge No 
SQL Yes 
SSIS Integration Toolkit No 
Streamkap No 
Tad No 
Tenzir No 

Integrations

SDF Yes 
3LC Yes 
Amazon Data Firehose Yes 
Amazon SageMaker Data Wrangler Yes 
Apache Arrow No 
Arroyo Yes 
Blotout Yes 
CSViewer Yes 
Google Cloud Storage No 
GribStream Yes 
IBM Db2 Event Store Yes 
MLJAR Studio Yes 
OpenObserve Yes 
OrcaSheets Yes 
QuerySurge Yes 
SQL No 
SSIS Integration Toolkit Yes 
Streamkap Yes 
Tad Yes 
Tenzir Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

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 No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours Yes 
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 Yes 

Types of Training

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

Vendor Details

Company Name

Apache Software Foundation

Founded

2019

Country

United States

Website

datafusion.apache.org

Vendor Details

Company Name

The Apache Software Foundation

Founded

1999

Country

United States

Website

parquet.apache.org

Product Features

Database

Backup and Recovery No 
Creation / Development No 
Data Migration No 
Data Replication No 
Data Search No 
Data Security No 
Database Conversion No 
Mobile Access No 
Monitoring No 
NOSQL No 
Performance Analysis No 
Queries No 
Relational Interface No 
Virtualization No 

Product Features

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