Spark Streaming

Spark Streaming

Apache Software Foundation
+
+

Related Products

  • Teradata VantageCloud
    1,124 Ratings
    Visit Website
  • dbt
    263 Ratings
    Visit Website
  • DataBuck
    6 Ratings
    Visit Website
  • Google Cloud BigQuery
    2,023 Ratings
    Visit Website
  • Gemini Enterprise Agent Platform
    999 Ratings
    Visit Website
  • Qloo
    23 Ratings
    Visit Website
  • Apify
    1,441 Ratings
    Visit Website
  • Google Cloud Platform
    61,023 Ratings
    Visit Website
  • TinyPNG
    67 Ratings
    Visit Website
  • Denodo
    387 Ratings
    Visit Website

About

Daft is a framework for ETL, analytics and ML/AI at scale. Its familiar Python dataframe API is built to outperform Spark in performance and ease of use. Daft plugs directly into your ML/AI stack through efficient zero-copy integrations with essential Python libraries such as Pytorch and Ray. It also allows requesting GPUs as a resource for running models. Daft runs locally with a lightweight multithreaded backend. When your local machine is no longer sufficient, it scales seamlessly to run out-of-core on a distributed cluster. Daft can handle User-Defined Functions (UDFs) in columns, allowing you to apply complex expressions and operations to Python objects with the full flexibility required for ML/AI. Daft runs locally with a lightweight multithreaded backend. When your local machine is no longer sufficient, it scales seamlessly to run out-of-core on a distributed cluster.

About

Spark Streaming brings Apache Spark's language-integrated API to stream processing, letting you write streaming jobs the same way you write batch jobs. It supports Java, Scala and Python. Spark Streaming recovers both lost work and operator state (e.g. sliding windows) out of the box, without any extra code on your part. By running on Spark, Spark Streaming lets you reuse the same code for batch processing, join streams against historical data, or run ad-hoc queries on stream state. Build powerful interactive applications, not just analytics. Spark Streaming is developed as part of Apache Spark. It thus gets tested and updated with each Spark release. You can run Spark Streaming on Spark's standalone cluster mode or other supported cluster resource managers. It also includes a local run mode for development. In production, Spark Streaming uses ZooKeeper and HDFS for high availability.

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

Developers and enterprises in search of a solution to manage their multimodal data

Audience

Real-Time Data Streaming solution for businesses

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

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

Review this Software

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

Daft
United States
www.getdaft.io

Company Information

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

Alternatives

Alternatives

ksqlDB

ksqlDB

Confluent
Samza

Samza

Apache Software Foundation
Apache Spark

Apache Spark

Apache Software Foundation
MLlib

MLlib

Apache Software Foundation

Categories

Categories

Integrations

Apache Spark
Amazon Web Services (AWS)
Apache Arrow
Apache Iceberg
Databricks
Delta Lake
Google Cloud Platform
JSON
Microsoft Azure
PubSub+ Platform
PyTorch
Python
Rust
Unity Catalog
pandas

Integrations

Apache Spark
Amazon Web Services (AWS)
Apache Arrow
Apache Iceberg
Databricks
Delta Lake
Google Cloud Platform
JSON
Microsoft Azure
PubSub+ Platform
PyTorch
Python
Rust
Unity Catalog
pandas
Claim Daft and update features and information
Claim Daft and update features and information
Claim Spark Streaming and update features and information
Claim Spark Streaming and update features and information