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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

Oracle Cloud Infrastructure (OCI) Data Flow is a comprehensive managed service for Apache Spark, enabling users to execute processing tasks on enormous data sets without the burden of deploying or managing infrastructure. This capability accelerates the delivery of applications, allowing developers to concentrate on building their apps rather than dealing with infrastructure concerns. OCI Data Flow autonomously manages the provisioning of infrastructure, network configurations, and dismantling after Spark jobs finish. It also oversees storage and security, significantly reducing the effort needed to create and maintain Spark applications for large-scale data analysis. Furthermore, with OCI Data Flow, there are no clusters that require installation, patching, or upgrading, which translates to both time savings and reduced operational expenses for various projects. Each Spark job is executed using private dedicated resources, which removes the necessity for prior capacity planning. Consequently, organizations benefit from a pay-as-you-go model, only incurring costs for the infrastructure resources utilized during the execution of Spark jobs. This innovative approach not only streamlines the process but also enhances scalability and flexibility for data-driven applications.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amundsen Yes 
Apache HBase Yes 
Apache Mahout Yes 
Astro by Astronomer Yes 
BentoML Yes 
Dagster Yes 
Deep.BI Yes 
IBM watsonx.data Yes 
Kestra Yes 
Metabase Yes 
NVMesh Yes 
Okera Yes 
Oracle Cloud Infrastructure Data Flow Yes 
Quorso Yes 
Snowflake CoCo Yes 
Xtendlabs Yes 
Zepl Yes 
doolytic Yes 
geoblink Yes 

Integrations

Amundsen No 
Apache HBase No 
Apache Mahout No 
Astro by Astronomer No 
BentoML No 
Dagster No 
Deep.BI No 
IBM watsonx.data No 
Kestra No 
Metabase No 
NVMesh No 
Okera No 
Oracle Cloud Infrastructure Data Flow No 
Quorso No 
Snowflake CoCo No 
Xtendlabs No 
Zepl No 
doolytic No 
geoblink No 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Pricing Details

$0.0085 per GB per hour
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 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 No 

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

spark.apache.org

Vendor Details

Company Name

Oracle

Founded

1977

Country

United States

Website

www.oracle.com/big-data/data-flow/

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 

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 Science

Access Control No 
Advanced Modeling No 
Audit Logs No 
Data Discovery No 
Data Ingestion No 
Data Preparation No 
Data Visualization No 
Model Deployment No 
Reports No 

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