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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Impala offers rapid response times and accommodates numerous concurrent users for business intelligence and analytical inquiries within the Hadoop ecosystem, supporting technologies such as Iceberg, various open data formats, and multiple cloud storage solutions. Additionally, it exhibits linear scalability, even when deployed in environments with multiple tenants. The platform seamlessly integrates with Hadoop's native security measures and employs Kerberos for user authentication, while the Ranger module provides a means to manage permissions, ensuring that only authorized users and applications can access specific data. You can leverage the same file formats, data types, metadata, and frameworks for security and resource management as those used in your Hadoop setup, avoiding unnecessary infrastructure and preventing data duplication or conversion. For users familiar with Apache Hive, Impala is compatible with the same metadata and ODBC driver, streamlining the transition. It also supports SQL, which eliminates the need to develop a new implementation from scratch. With Impala, a greater number of users can access and analyze a wider array of data through a unified repository, relying on metadata that tracks information right from the source to analysis. This unified approach enhances efficiency and optimizes data accessibility across various applications.

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 No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

3forge Yes 
Apache Hive Yes 
Apache Iceberg Yes 
Hadoop Yes 
Inferyx Yes 
SQL Yes 
Amazon EC2 No 
Apache Phoenix No 
Determined AI No 
IBM Analytics Engine No 
Jupyter Notebook No 
JupyterLab No 
LogIsland No 
Medical LLM No 
Okera No 
Prodea No 
Spark Streaming No 
Unravel No 
Warp 10 No 

Integrations

3forge Yes 
Apache Hive Yes 
Apache Iceberg Yes 
Hadoop Yes 
Inferyx Yes 
SQL Yes 
Amazon EC2 Yes 
Apache Phoenix Yes 
Determined AI Yes 
IBM Analytics Engine Yes 
Jupyter Notebook Yes 
JupyterLab Yes 
LogIsland Yes 
Medical LLM Yes 
Okera Yes 
Prodea Yes 
Spark Streaming Yes 
Unravel Yes 
Warp 10 Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
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 No 
Live Rep (24/7) No 
Online Support No 

Types of Training

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

Types of Training

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

Vendor Details

Company Name

Apache

Country

United States

Website

impala.apache.org

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

spark.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

Big Data

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

Data Analysis

Data Discovery No 
Data Visualization No 
High Volume Processing No 
Predictive Analytics No 
Regression Analysis No 
Sentiment Analysis No 
Statistical Modeling No 
Text Analytics No 

Streaming Analytics

Data Enrichment Yes 
Data Wrangling / Data Prep Yes 
Multiple Data Source Support Yes 
Process Automation Yes 
Real-time Analysis / Reporting No 
Visualization Dashboards No 

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