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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

BigBI empowers data professionals to create robust big data pipelines in an interactive and efficient manner, all without requiring any programming skills. By harnessing the capabilities of Apache Spark, BigBI offers remarkable benefits such as scalable processing of extensive datasets, achieving speeds that can be up to 100 times faster. Moreover, it facilitates the seamless integration of conventional data sources like SQL and batch files with contemporary data types, which encompass semi-structured formats like JSON, NoSQL databases, Elastic, and Hadoop, as well as unstructured data including text, audio, and video. Additionally, BigBI supports the amalgamation of streaming data, cloud-based information, artificial intelligence/machine learning, and graphical data, making it a comprehensive tool for data management. This versatility allows organizations to leverage diverse data types and sources, enhancing their analytical capabilities significantly.

Description

MLlib, the machine learning library of Apache Spark, is designed to be highly scalable and integrates effortlessly with Spark's various APIs, accommodating programming languages such as Java, Scala, Python, and R. It provides an extensive range of algorithms and utilities, which encompass classification, regression, clustering, collaborative filtering, and the capabilities to build machine learning pipelines. By harnessing Spark's iterative computation features, MLlib achieves performance improvements that can be as much as 100 times faster than conventional MapReduce methods. Furthermore, it is built to function in a variety of environments, whether on Hadoop, Apache Mesos, Kubernetes, standalone clusters, or within cloud infrastructures, while also being able to access multiple data sources, including HDFS, HBase, and local files. This versatility not only enhances its usability but also establishes MLlib as a powerful tool for executing scalable and efficient machine learning operations in the Apache Spark framework. The combination of speed, flexibility, and a rich set of features renders MLlib an essential resource for data scientists and engineers alike.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

No images available

Screenshots View All

Integrations

Apache Cassandra Yes 
Apache Hive Yes 
Hadoop Yes 
Amazon Redshift Yes 
Amazon S3 Yes 
Apache Kafka Yes 
Apache Kudu Yes 
Cloudera Yes 
Elasticsearch Yes 
Google Cloud BigQuery Yes 
Java No 
MongoDB Yes 
Neo4j Yes 
PostgreSQL Yes 
Python No 
R No 
RabbitMQ Yes 
SQL Server Yes 
Salesforce Yes 
Scala No 

Integrations

Apache Cassandra Yes 
Apache Hive Yes 
Hadoop Yes 
Amazon Redshift No 
Amazon S3 No 
Apache Kafka No 
Apache Kudu No 
Cloudera No 
Elasticsearch No 
Google Cloud BigQuery No 
Java Yes 
MongoDB No 
Neo4j No 
PostgreSQL No 
Python Yes 
R Yes 
RabbitMQ No 
SQL Server No 
Salesforce No 
Scala 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 Yes 
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 Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

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

Types of Training

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

Vendor Details

Company Name

BigBI

Founded

2019

Country

Israel

Website

bigbi.io

Vendor Details

Company Name

Apache Software Foundation

Founded

1995

Country

United States

Website

spark.apache.org/mllib/

Product Features

Business Intelligence

Ad Hoc Reports No 
Benchmarking No 
Budgeting & Forecasting No 
Dashboard No 
Data Analysis No 
Key Performance Indicators No 
Natural Language Generation (NLG) No 
Performance Metrics No 
Predictive Analytics No 
Profitability Analysis No 
Strategic Planning No 
Trend / Problem Indicators No 
Visual Analytics No 

ETL

Data Analysis No 
Data Filtering No 
Data Quality Control No 
Job Scheduling No 
Match & Merge No 
Metadata Management No 
Non-Relational Transformations No 
Version Control No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

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