Spark Streaming

Spark Streaming

Apache Software Foundation
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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.

About

Spark.work is a platform that unites HR Management (HRMS) and Strategy Execution. Designed for growing companies, Spark helps leaders gain clarity and efficiency in people operations, then leverages that foundation to align and execute strategy across the organization. What Spark.work Offers Spark simplifies HR processes while connecting them directly to business goals: People Management: Centralized employee data, leave and attendance tracking, onboarding/offboarding workflows, document management, and visual organization charts. Talent & Growth: Applicant Tracking System (ATS), performance reviews, employee feedback, and development planning. Strategy & Performance: Strategy maps, OKRs, KPIs, and initiatives — all linked back to people and teams. AI Assistance: Smart agents that support KPI/OKR setup, surface insights, and automate repetitive tasks.

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

Real-Time Data Streaming solution for businesses

Audience

Spark.work can be used by IT, banking, telecom, insurance, and service companies. It’s built for CEOs, COOs, CHROs, and HR teams who want one integrated solution to manage both people and performance.

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

$1.5 month/per user
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

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

Company Information

Spark.work
Founded: 2019
Armenia
spark.work/

Alternatives

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ksqlDB

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WorkforceHub

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MLlib

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Categories

Categories

Human Resources Features

360 Degree Feedback
Applicant Tracking
Attendance Management
Benefits Management
Career Development Planning
Compensation Management
Compliance Management
Employee Database
Employee Lifecycle Management
Onboarding
Payroll Management
Performance Management
Recruiting Management
Self Service Portal
Succession Planning
Time & Attendance Management
Time Off Management
Timesheets
Training Management

Integrations

Apache Spark
Bravo for Power BI
ChatGPT
Google Chrome
Google Workspace
Microsoft 365
PubSub+ Platform

Integrations

Apache Spark
Bravo for Power BI
ChatGPT
Google Chrome
Google Workspace
Microsoft 365
PubSub+ Platform
Claim Spark Streaming and update features and information
Claim Spark Streaming and update features and information
Claim Spark.work and update features and information
Claim Spark.work and update features and information