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Description
Apache Ivy™ serves as a widely-used dependency manager that emphasizes both flexibility and ease of use. Discover its distinct enterprise capabilities, user feedback, and the ways it can enhance your build process! Ivy operates as a tool designed for the management of project dependencies, which includes recording, tracking, resolving, and reporting. It is not confined to any specific methodology or framework, allowing it to be highly adaptable to various dependency management and build workflows. Although it can function independently, Ivy is particularly effective in conjunction with Apache Ant, offering a variety of robust Ant tasks that range from resolving dependencies to generating reports and facilitating publication. Among its many powerful attributes, users often highlight its flexibility, seamless integration with Ant, and an efficient engine for managing transitive dependencies. Additionally, Ivy is an open-source tool, distributed under a permissive Apache License, making it accessible for a wide audience. This combination of features positions Ivy as a valuable asset for developers seeking to streamline their dependency management processes.
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.
API Access
Has API
API Access
Has API
Integrations
Apache Phoenix
Azure Data Factory
DQOps
Determined AI
Google Cloud Managed Service for Apache Spark
JFrog
Kestra
Lightbits
MLflow
Mage Sensitive Data Discovery
Integrations
Apache Phoenix
Azure Data Factory
DQOps
Determined AI
Google Cloud Managed Service for Apache Spark
JFrog
Kestra
Lightbits
MLflow
Mage Sensitive Data Discovery
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
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
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
Vendor Details
Company Name
Apache Software Foundation
Country
United States
Website
ant.apache.org/ivy/
Vendor Details
Company Name
Apache Software Foundation
Founded
1999
Country
United States
Website
spark.apache.org
Product Features
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