Apache Spark

Apache Spark

Apache Software Foundation
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About

Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.

About

Oracle Cloud Infrastructure (OCI) Data Flow is a fully managed Apache Spark service to perform processing tasks on extremely large data sets without infrastructure to deploy or manage. This enables rapid application delivery because developers can focus on app development, not infrastructure management. OCI Data Flow handles infrastructure provisioning, network setup, and teardown when Spark jobs are complete. Storage and security are also managed, which means less work is required for creating and managing Spark applications for big data analysis. With OCI Data Flow, there are no clusters to install, patch, or upgrade, which saves time and operational costs for projects. OCI Data Flow runs each Spark job in private dedicated resources, eliminating the need for upfront capacity planning. With OCI Data Flow, IT only needs to pay for the infrastructure resources that Spark jobs use while they are running.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Organizations that want a unified analytics engine for large-scale data processing

Audience

Organizations looking for a data science solution

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

$0.0085 per GB per hour
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Apache Software Foundation
Founded: 1999
United States
spark.apache.org

Company Information

Oracle
Founded: 1977
United States
www.oracle.com/big-data/data-flow/

Alternatives

dbt

dbt

dbt Labs

Alternatives

E-MapReduce

E-MapReduce

Alibaba
AWS Glue

AWS Glue

Amazon
Amazon EMR

Amazon EMR

Amazon
MLlib

MLlib

Apache Software Foundation
Apache Spark

Apache Spark

Apache Software Foundation

Categories

Categories

Streaming Analytics Features

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

Integrations

Alibaba Log Service
Apache Hive
Apache Mahout
Azure Data Factory
DataHub
Determined AI
Flyte
Gable
HStreamDB
IBM Databand
Querona
RazorThink
Saagie
Spark Streaming
StreamFlux
Tonic
Tonic Ephemeral
VeloDB
matchit

Integrations

Alibaba Log Service
Apache Hive
Apache Mahout
Azure Data Factory
DataHub
Determined AI
Flyte
Gable
HStreamDB
IBM Databand
Querona
RazorThink
Saagie
Spark Streaming
StreamFlux
Tonic
Tonic Ephemeral
VeloDB
matchit
Claim Apache Spark and update features and information
Claim Apache Spark and update features and information
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