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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

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Description

Apache Spark™ serves as a comprehensive analytics platform designed for large-scale data processing. It delivers exceptional performance for both batch and streaming data by employing an advanced Directed Acyclic Graph (DAG) scheduler, a sophisticated query optimizer, and a robust execution engine. With over 80 high-level operators available, Spark simplifies the development of parallel applications. Additionally, it supports interactive use through various shells including Scala, Python, R, and SQL. Spark supports a rich ecosystem of libraries such as SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming, allowing for seamless integration within a single application. It is compatible with various environments, including Hadoop, Apache Mesos, Kubernetes, and standalone setups, as well as cloud deployments. Furthermore, Spark can connect to a multitude of data sources, enabling access to data stored in systems like HDFS, Alluxio, Apache Cassandra, Apache HBase, and Apache Hive, among many others. This versatility makes Spark an invaluable tool for organizations looking to harness the power of large-scale data analytics.

Description

Polars offers a comprehensive Python API that reflects common data wrangling practices, providing a wide array of functionalities for manipulating DataFrames through an expression language that enables the creation of both efficient and clear code. Developed in Rust, Polars makes deliberate choices to ensure a robust DataFrame API that caters to the Rust ecosystem's needs. It serves not only as a library for DataFrames but also as a powerful backend query engine for your data models, allowing for versatility in data handling and analysis. This flexibility makes it a valuable tool for data scientists and engineers alike.

Description

You can develop on your laptop, then scale the same Python code elastically across hundreds or GPUs on any cloud. Ray converts existing Python concepts into the distributed setting, so any serial application can be easily parallelized with little code changes. With a strong ecosystem distributed libraries, scale compute-heavy machine learning workloads such as model serving, deep learning, and hyperparameter tuning. Scale existing workloads (e.g. Pytorch on Ray is easy to scale by using integrations. Ray Tune and Ray Serve native Ray libraries make it easier to scale the most complex machine learning workloads like hyperparameter tuning, deep learning models training, reinforcement learning, and training deep learning models. In just 10 lines of code, you can get started with distributed hyperparameter tune. Creating distributed apps is hard. Ray is an expert in distributed execution.

API Access

Has API

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Screenshots View All

Integrations

Flyte
Acxiom Real Identity
Amazon EC2 Trn2 Instances
Amazon EMR
Amazon SageMaker Data Wrangler
BigLake
Deeplearning4j
Great Expectations
Hadoop
IBM Analytics Engine
Lyftrondata
Mage Static Data Masking
NVIDIA RAPIDS
Onehouse
Precisely Connect
Prophecy
Quantexa
Rational BI
Telmai
doolytic

Integrations

Flyte
Acxiom Real Identity
Amazon EC2 Trn2 Instances
Amazon EMR
Amazon SageMaker Data Wrangler
BigLake
Deeplearning4j
Great Expectations
Hadoop
IBM Analytics Engine
Lyftrondata
Mage Static Data Masking
NVIDIA RAPIDS
Onehouse
Precisely Connect
Prophecy
Quantexa
Rational BI
Telmai
doolytic

Integrations

Flyte
Acxiom Real Identity
Amazon EC2 Trn2 Instances
Amazon EMR
Amazon SageMaker Data Wrangler
BigLake
Deeplearning4j
Great Expectations
Hadoop
IBM Analytics Engine
Lyftrondata
Mage Static Data Masking
NVIDIA RAPIDS
Onehouse
Precisely Connect
Prophecy
Quantexa
Rational BI
Telmai
doolytic

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

spark.apache.org

Vendor Details

Company Name

Polars

Website

www.pola.rs/

Vendor Details

Company Name

Anyscale

Founded

2019

Country

United States

Website

ray.io

Product Features

Big Data

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

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Streaming Analytics

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

Product Features

Big Data

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

Product Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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