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Apache Spark VS Aware360

Compare Apache Spark VS Aware360 and see what are their differences

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Apache Spark logo Apache Spark

Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

Aware360 logo Aware360

real time data. real time decisions.
  • Apache Spark Landing page
    Landing page //
    2021-12-31
  • Aware360 Landing page
    Landing page //
    2023-08-25

Aware360 understands people are the most important part of any workplace and provides the tools to keep employees safe throughout their day. Driven by our passion for people, the Aware360 suite of safety solutions leverages personal technology such as smartphones, wearables and satellite devices to keep people safe and productive.

Apache Spark features and specs

  • Speed
    Apache Spark processes data in-memory, significantly increasing the processing speed of data tasks compared to traditional disk-based engines.
  • Ease of Use
    Spark offers high-level APIs in Java, Scala, Python, and R, making it accessible to a broad range of developers and data scientists.
  • Advanced Analytics
    Spark supports advanced analytics, including machine learning, graph processing, and real-time streaming, which can be executed in the same application.
  • Scalability
    Spark can handle both small- and large-scale data processing tasks, scaling seamlessly from a single machine to thousands of servers.
  • Support for Various Data Sources
    Spark can integrate with a wide variety of data sources, including HDFS, Apache HBase, Apache Hive, Cassandra, and many others.
  • Active Community
    Spark has a vibrant and active community, providing a wealth of extensions, tools, and support options.

Possible disadvantages of Apache Spark

  • Memory Consumption
    Spark's in-memory processing can be resource-intensive, requiring substantial amounts of RAM, which can drive up costs for large-scale deployments.
  • Complexity in Configuration
    To optimize performance, Spark requires careful configuration and tuning, which can be complex and time-consuming.
  • Learning Curve
    Despite its ease of use, mastering the full range of Spark's features and best practices can take considerable time and effort.
  • Latency for Small Data
    For smaller datasets or low-latency requirements, Spark might not be the most efficient choice, as other technologies could offer better performance.
  • Integration Overhead
    Though Spark integrates with many systems, incorporating it into an existing data infrastructure can introduce additional overhead and complexity.
  • Community Support Variability
    While the community is active, the support and quality of third-party libraries and tools can be inconsistent, leading to potential challenges in implementation.

Aware360 features and specs

  • Comprehensive Safety Solution
    SafetyAware offers a comprehensive safety solution for workers by integrating various tools and technologies to ensure their well-being in the workplace. The platform provides real-time monitoring and alerts, which can help prevent accidents and respond to emergencies quickly.
  • Scalability
    The platform is scalable, which makes it suitable for businesses of all sizes. Whether managing the safety of a small team or a large workforce, SafetyAware can adapt to the company's needs without compromising on functionality.
  • Ease of Use
    SafetyAware is designed with user-friendliness in mind, making it easy for both workers and employers to navigate the system. The intuitive interface reduces the learning curve and ensures higher adoption rates across organizations.
  • Real-time Alerts
    The system provides real-time alerts that notify management and emergency services in case of accidents or risks, enabling quicker response times and potentially reducing the severity of incidents.

Possible disadvantages of Aware360

  • Cost Considerations
    While SafetyAware offers valuable features, the cost may be prohibitive for small businesses or companies with limited budgets. The investment in technology and training could be substantial.
  • Potential for Over-reliance on Technology
    Relying heavily on technology for safety might result in reduced human oversight. There's a risk that workers might become less vigilant if they depend solely on the system to manage safety hazards.
  • Implementation Complexity
    Integrating SafetyAware into an existing safety management framework can be complex and time-consuming, requiring dedicated resources for setup and ongoing management.
  • Dependence on Connectivity
    The effectiveness of SafetyAware is largely dependent on reliable internet connectivity, which may not always be available in remote or rural work locations. This could limit the system's ability to provide real-time alerts and monitoring.

Apache Spark videos

+ Add

Weekly Apache Spark live Code Review -- look at StringIndexer multi-col (Scala) & Python testing

More videos:

  • Review - What's New in Apache Spark 3.0.0
  • Review - Apache Spark for Data Engineering and Analysis - Overview

Aware360 videos

+ Add

SafetyLink Band and the Aware360 App

Category Popularity

0-100% (relative to Apache Spark and Aware360)

Apache Spark

Aware360

Databases
100 100%
Databases
0% 0
Workplace Safety
0 0%
Workplace Safety
100% 100
Big Data
100 100%
Big Data
0% 0
Communication
0 0%
Communication
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Spark and Aware360

Apache Spark Reviews

15 data science tools to consider using in 2021
Apache Spark is an open source data processing and analytics engine that can handle large amounts of data -- upward of several petabytes, according to proponents. Spark's ability to rapidly process data has fueled significant growth in the use of the platform since it was created in 2009, helping to make the Spark project one of the largest open source communities among big...
Source: searchbusinessanalytics.techtarget.com
Top 15 Kafka Alternatives Popular In 2021
Apache Spark is a well-known, general-purpose, open-source analytics engine for large-scale, core data processing. It is known for its high-performance quality for data processing – batch and streaming with the help of its DAG scheduler, query optimizer, and engine. Data streams are processed in real-time and hence it is quite fast and efficient. Its machine learning...
Source: www.spec-india.com
5 Best-Performing Tools that Build Real-Time Data Pipeline
Apache Spark is an open-source and flexible in-memory framework which serves as an alternative to map-reduce for handling batch, real-time analytics and data processing workloads. It provides native bindings for the Java, Scala, Python, and R programming languages, and supports SQL, streaming data, machine learning and graph processing. From its beginning in the AMPLab at...
Source: www.analyticsinsight.net

Aware360 Reviews

We have no reviews of Aware360 yet.
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Social recommendations and mentions

Based on our record, Apache Spark seems to be more popular. It has been mentiond 70 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Apache Spark mentions (70)

  • Every Database Will Support Iceberg — Here's Why
    Apache Iceberg defines a table format that separates how data is stored from how data is queried. Any engine that implements the Iceberg integration — Spark, Flink, Trino, DuckDB, Snowflake, RisingWave — can read and/or write Iceberg data directly. - Source: dev.to / 29 days ago
  • How to Reduce Big Data Analytics Costs by 90% with Karpenter and Spark
    Apache Spark powers large-scale data analytics and machine learning, but as workloads grow exponentially, traditional static resource allocation leads to 30–50% resource waste due to idle Executors and suboptimal instance selection. - Source: dev.to / about 1 month ago
  • Unveiling the Apache License 2.0: A Deep Dive into Open Source Freedom
    One of the key attributes of Apache License 2.0 is its flexible nature. Permitting use in both proprietary and open source environments, it has become the go-to choice for innovative projects ranging from the Apache HTTP Server to large-scale initiatives like Apache Spark and Hadoop. This flexibility is not solely legal; it is also philosophical. The license is designed to encourage transparency and maintain a... - Source: dev.to / 2 months ago
  • The Application of Java Programming In Data Analysis and Artificial Intelligence
    [1] S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach. Pearson, 2020. [2] F. Chollet, Deep Learning with Python. Manning Publications, 2018. [3] C. C. Aggarwal, Data Mining: The Textbook. Springer, 2015. [4] J. Dean and S. Ghemawat, "MapReduce: Simplified Data Processing on Large Clusters," Communications of the ACM, vol. 51, no. 1, pp. 107-113, 2008. [5] Apache Software Foundation, "Apache... - Source: dev.to / 2 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    If you're designing an event-based pipeline, you can use a data streaming tool like Kafka to process data as it's collected by the pipeline. For a setup that already has data stored, you can use tools like Apache Spark to batch process and clean it before moving ahead with the pipeline. - Source: dev.to / 3 months ago
View more

Aware360 mentions (0)

We have not tracked any mentions of Aware360 yet. Tracking of Aware360 recommendations started around Mar 2021.

What are some alternatives?

When comparing Apache Spark and Aware360, you can also consider the following products

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

Eagle.io - Cloud-based environmental IoT platform

Hadoop - Open-source software for reliable, scalable, distributed computing

EtQ EHS Software - EtQ EHS Software is the leading Electronic Health and Safety Compliance Management Software that is used across the globe by industrial organizations to manage safety compliance and environmental regulations.

Apache Storm - Apache Storm is a free and open source distributed realtime computation system.

Perillon - Perillon is an EHS software that helps companies to achieve compliance with the relevant government rules and regulations.

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