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

Unlock insights from all your data and build artificial intelligence (AI) solutions with Azure Databricks, set up your Apache Spark™ environment in minutes, autoscale, and collaborate on shared projects in an interactive workspace. Azure Databricks supports Python, Scala, R, Java, and SQL, as well as data science frameworks and libraries including TensorFlow, PyTorch, and scikit-learn. Azure Databricks provides the latest versions of Apache Spark and allows you to seamlessly integrate with open source libraries. Spin up clusters and build quickly in a fully managed Apache Spark environment with the global scale and availability of Azure. Clusters are set up, configured, and fine-tuned to ensure reliability and performance without the need for monitoring. Take advantage of autoscaling and auto-termination to improve total cost of ownership (TCO).

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

Companies in need of a big data 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

No information available.
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

Microsoft
Founded: 1975
United States
azure.microsoft.com/en-us/services/databricks/

Alternatives

AWS Glue

AWS Glue

Amazon

Alternatives

Amazon EMR

Amazon EMR

Amazon
Apache Spark

Apache Spark

Apache Software Foundation
Amazon EMR

Amazon EMR

Amazon

Categories

Categories

Streaming Analytics Features

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

Integrations

Activeeon ProActive
Azure Marketplace
DQOps
Dagster
Databricks Data Intelligence Platform
HStreamDB
Kedro
Mage Platform
Mage Sensitive Data Discovery
Medical LLM
ModelOp
Prophecy
Protegrity
Qlik Staige
Sifflet
Tabular
Tonic Ephemeral
Union Cloud
ZenML
definity

Integrations

Activeeon ProActive
Azure Marketplace
DQOps
Dagster
Databricks Data Intelligence Platform
HStreamDB
Kedro
Mage Platform
Mage Sensitive Data Discovery
Medical LLM
ModelOp
Prophecy
Protegrity
Qlik Staige
Sifflet
Tabular
Tonic Ephemeral
Union Cloud
ZenML
definity
Claim Apache Spark and update features and information
Claim Apache Spark and update features and information
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