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Apache Spark VS AWS CloudTrail

Compare Apache Spark VS AWS CloudTrail 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.

AWS CloudTrail logo AWS CloudTrail

AWS CloudTrail is a web service that records AWS API calls for your account and delivers log files to you.
  • Apache Spark Landing page
    Landing page //
    2021-12-31
  • AWS CloudTrail Landing page
    Landing page //
    2023-04-18

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.

AWS CloudTrail features and specs

  • Comprehensive Logging
    AWS CloudTrail provides detailed logging of all API calls made within your AWS environment, helping you maintain accountability and transparency.
  • Enhanced Security
    By logging activities, CloudTrail helps in detecting unusual behavior and potential security threats, allowing for timely response.
  • Compliance and Auditing
    CloudTrail logs are crucial for regulatory compliance and auditing purposes, supporting frameworks such as HIPAA, GDPR, and PCI DSS.
  • Integration
    CloudTrail integrates seamlessly with other AWS services like CloudWatch and AWS Lambda, enabling automated responses to specific activities.
  • Event History
    Access historical event records for your AWS account, enabling analysis and troubleshooting of past issues.
  • Data Retention
    CloudTrail allows you to define policies for retaining log data, ensuring that logs are available as long as needed for audits and investigations.

Possible disadvantages of AWS CloudTrail

  • Costs
    While CloudTrail's basic tier is free, there are costs associated with advanced features and long-term log storage, which can add up for large organizations.
  • Complexity
    Managing and analyzing a large volume of logs can become complex and time-consuming, especially without additional tools and expertise.
  • Performance Impact
    While minimal, there may be a slight performance overhead associated with logging large volumes of AWS API calls.
  • Incomplete Coverage
    Not all AWS services and features support CloudTrail logging, potentially leaving gaps in visibility for certain activities.
  • Latency
    There is some latency involved in the delivery of log data, which might delay real-time monitoring and response in critical scenarios.
  • Data Exposure Risk
    If not properly secured, CloudTrail logs themselves could become a target for attackers seeking sensitive information about your AWS environment.

Analysis of Apache Spark

Overall verdict

  • Yes, Apache Spark is generally considered good, especially for organizations and individuals that require efficient and fast data processing capabilities. It is well-supported, frequently updated, and widely adopted in the industry, making it a reliable choice for big data solutions.

Why this product is good

  • Apache Spark is highly valued because it provides a fast and general-purpose cluster-computing framework for big data processing. It offers extensive libraries for SQL, streaming, machine learning, and graph processing, making it versatile for various data processing needs. Its in-memory computing capability boosts the processing speed significantly compared to traditional disk-based processing. Additionally, Spark integrates well with Hadoop and other big data tools, providing a seamless ecosystem for large-scale data analysis.

Recommended for

  • Data scientists and engineers working with large datasets.
  • Organizations leveraging machine learning and analytics for decision-making.
  • Businesses needing real-time data processing capabilities.
  • Developers looking to integrate with Hadoop ecosystems.
  • Teams requiring robust support for multiple data sources and formats.

Analysis of AWS CloudTrail

Overall verdict

  • AWS CloudTrail is generally considered a good service due to its robust tracking and logging capabilities, aiding in security and compliance. It is highly regarded by users for its ease of integration with other AWS services and comprehensive audit trail offerings.

Why this product is good

  • AWS CloudTrail is a valuable service for tracking and logging activity across your AWS infrastructure. It enhances security and compliance by providing visibilities into API calls and actions taken in your AWS account, facilitating the monitoring and auditing of user activity. CloudTrail helps detect unusual behavior and unauthorized access, making it a reliable tool for ensuring governance and maintaining the operational integrity of your environment.

Recommended for

  • Organizations required to adhere to regulatory compliance standards
  • Teams responsible for security operations and incident response
  • DevOps engineers monitoring API activity and infrastructure changes
  • Businesses seeking to improve governance across their AWS resources

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

AWS CloudTrail videos

+ Add

AWS Cloudtrail vs Cloudwatch in 15 minutes | AWS tutorial for beginners

More videos:

  • Review - AWS re:Invent 2018: Augmenting Security & Improving Operational Health w/ AWS CloudTrail (SEC323)

Category Popularity

0-100% (relative to Apache Spark and AWS CloudTrail)

Apache Spark

AWS CloudTrail

Databases
100 100%
Databases
0% 0
API Tools
0 0%
API Tools
100% 100
Big Data
100 100%
Big Data
0% 0
APIs
0 0%
APIs
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 AWS CloudTrail

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

AWS CloudTrail Reviews

We have no reviews of AWS CloudTrail yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Apache Spark should be more popular than AWS CloudTrail. 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 / about 2 months 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 2 months 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 / 3 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 / 3 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 / 4 months ago
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AWS CloudTrail mentions (16)

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What are some alternatives?

When comparing Apache Spark and AWS CloudTrail, 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.

Postman - The Collaboration Platform for API Development

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

DreamFactory - DreamFactory is an API management platform used to generate, secure, document, and extend APIs.

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

Sentinet - API Management and SOA Governance for enterprises and developers

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