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Apache Spark VS SigmaPlot

Compare Apache Spark VS SigmaPlot 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.

SigmaPlot logo SigmaPlot

SigmaPlot is a scientific data analysis and graphing software package with an intuitive interface for all your statistical analysis and graphing needs that takes you beyond simple spreadsheets and helps you to produce high-quality graphs without …
  • Apache Spark Landing page
    Landing page //
    2021-12-31
  • SigmaPlot Landing page
    Landing page //
    2022-12-13

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.

SigmaPlot features and specs

  • Advanced Graphical Capabilities
    SigmaPlot offers a wide range of graph types and advanced plotting features, allowing for detailed and highly customized visual representation of data.
  • Data Analysis Tools
    The software includes robust data analysis tools, such as curve fitting and regression analysis, that help in extracting meaningful insights from data sets.
  • Integration with Microsoft Office
    SigmaPlot seamlessly integrates with Microsoft Office, making it easy to incorporate graphs and data into presentations and documents.
  • User-friendly Interface
    It features a user-friendly interface that is relatively easy to navigate, which can help users, especially beginners, to work efficiently.
  • Template and Customization Options
    The program offers various templates and customization options for creating consistent and professional-looking graphs.

Possible disadvantages of SigmaPlot

  • Cost
    SigmaPlot is a premium software, which could be quite expensive for individuals and small organizations with limited budgets.
  • Steep Learning Curve
    Despite being user-friendly, mastering all the advanced features and capabilities of SigmaPlot can take considerable time and effort.
  • Limited Platform Support
    Primarily available for Windows, limiting its use for individuals and organizations using other operating systems like macOS and Linux.
  • Lack of Collaboration Features
    The software does not offer built-in collaboration tools, potentially making it challenging for teams to work together efficiently on data projects.
  • Resource Intensive
    Running SigmaPlot can be resource-intensive, which might pose challenges on lower-spec devices, affecting performance and productivity.

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

SigmaPlot videos

+ Add

SigmaPlot 12 Overview Presentation with Richard Mitchell / Systat Software

More videos:

  • Review - Performing a one-way ANOVA in SigmaPlot 13
  • Demo - SigmaPlot quick demo

Category Popularity

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

Apache Spark

SigmaPlot

Databases
100 100%
Databases
0% 0
Technical Computing
0 0%
Technical Computing
100% 100
Big Data
100 100%
Big Data
0% 0
Office & Productivity
0 0%
Office & Productivity
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 SigmaPlot

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

SigmaPlot Reviews

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

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 / 17 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 / 19 days 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 / about 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

SigmaPlot mentions (0)

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

What are some alternatives?

When comparing Apache Spark and SigmaPlot, 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.

GraphPad Prism - Overview. GraphPad Prism, available for both Windows and Mac computers, combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization.

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

OriginLab - OriginLab is a data analysis tool that provide the engineers and scientist with the technical charts and system for 2D and 3D plotting and all kind of fitting including curve and peak fitting.

Apache Hive - Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.

Azure Databricks - Azure Databricks is a fast, easy, and collaborative Apache Spark-based big data analytics service designed for data science and data engineering.

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