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Apache Spark VS Heap

Compare Apache Spark VS Heap 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.

Heap logo Heap

Analytics for web and iOS. Heap automatically captures every user action in your app and lets you measure it all. Clicks, taps, swipes, form submissions, page views, and more.
  • Apache Spark Landing page
    Landing page //
    2021-12-31
  • Heap Landing page
    Landing page //
    2023-10-05

Apache Spark

Website
spark.apache.org
Pricing URL
-
$ Details
Release Date
-
Edit details

Heap

Website
heap.io
Pricing URL
Official Heap Pricing
$ Details
-
Release Date
2013 January
Startup details
Country
United States
State
California
City
San Francisco
Founder(s)
Matin Movassate
Employees
100 - 249
Edit details

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.

Heap features and specs

  • Automatic Event Tracking
    Heap captures all user interactions automatically without requiring manual event setup, making it easier to get started and ensuring comprehensive data collection.
  • User-friendly Interface
    Heap provides a clean and intuitive interface, which allows non-technical users to easily create and analyze custom reports and dashboards.
  • Retroactive Analysis
    With Heap, users can define events at any time and view historical data, enabling analysis of past behaviors without prior configuration.
  • Comprehensive Data
    Heap collects a wide array of data points including clicks, form submissions, page views, and more, offering a holistic view of user interactions.
  • Integrations
    Heap offers robust integration capabilities with other analytics platforms, CRM systems, and data warehouses, facilitating seamless data flow between tools.

Possible disadvantages of Heap

  • Cost
    Heap can be expensive for smaller businesses or startups, particularly as the volume of tracked events and the number of users increases.
  • Learning Curve
    Despite its user-friendly interface, some users report a steep learning curve when it comes to leveraging Heap's more advanced features and capabilities.
  • Limited Customization
    While Heap provides a lot of data out-of-the-box, some users may find the customization options for tracking and reporting somewhat limited compared to other tools that offer more flexibility.
  • Data Redundancy
    The automatic tracking feature, while comprehensive, can sometimes lead to data redundancy or capturing irrelevant events, which may require additional data cleaning.
  • Reporting Complexity
    Some users have expressed that creating complex reports and funnels can be challenging and may require a deeper understanding of the platform's capabilities.

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

Heap videos

+ Add

Septimus Heap Series by Angie Sage || Spoiler Review

More videos:

  • Review - Fargo Season 1 Episode 8 "The Heap" Review
  • Review - Data Structures: Heaps

Category Popularity

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

Apache Spark

Heap

Databases
100 100%
Databases
0% 0
Analytics
0 0%
Analytics
100% 100
Big Data
100 100%
Big Data
0% 0
Web Analytics
0 0%
Web Analytics
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 Heap

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

Heap Reviews

10 Best Mixpanel Alternatives for Product Analytics in 2024
Heap is a web and mobile data analytics platform that captures every user interaction via secure session recording. Use it to get insights into customer behavior and to streamline your digital experiences. ⏩
Source: clickup.com
7 best Mixpanel alternatives to understand your users
On the other hand, Mixpanel requires you to manually define the events you want to track from the start. While this might take some extra time, it provides more detailed reports right off the bat, which makes the analysis straightforward. The choice between Heap and Mixpanel depends on whether you prioritize comprehensive data capturing (Heap) or a more detailed analysis...
Source: www.hotjar.com
Best Mixpanel Alternatives for SaaS
Heap is a robust product analytics platform that provides users with a plethora of in-depth insights into customer behavior and needs. With Heap, you can track user interactions in real time across all touch points within your product. Insights from Heap help you dig deeper into the paths users take when navigating your product and identify precise points of friction. Plus,...
Source: userpilot.com
Top 5 Plausible Analytics Alternatives in 2024
Additionally, Heap suggests reports for your review. You can define events, create segments, and utilize the event visualizer to delve into detailed user data.
Source: www.putler.com
Top 9 Plausible Analytics alternatives in 2024
Heap’s automatic event tracking and retroactive analytics offer a hassle-free approach, simplifying complex data analysis. Its user-friendly interface and intuitive tools enable effortless data exploration, offering detailed insights into user journeys without the need for manual tracking. Although it provides detailed user data, some users might find limitations in customer...
Source: usermaven.com

Social recommendations and mentions

Based on our record, Apache Spark should be more popular than Heap. 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 / 25 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 / 27 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 / 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

Heap mentions (11)

  • free-for.dev
    Heap.io — Automatically captures every user action in iOS or web apps. Free for up to 5,000 visits/month. - Source: dev.to / over 2 years ago
  • Question about testID in prod vs dev builds
    Check out Heap for React Native - https://heap.io. Source: over 2 years ago
  • All 2200+ companies in my db have a dedicated page now.
    How heavily does the site depend on heap.io for its core functionality? Like, say Heap went under completely out of the blue (god forbid) and you had to switch to Google analytics, how much tech debt are you in? Source: almost 3 years ago
  • Thousands of Popular Websites See What You Type–Before You Hit Submit
    Aren't services like Heap effectively worse versions of this? On their landing page they outright list this as their value prop: > Heap collects all the data on your customers - automatically. What they click. Where they go. What they do, even when you’re not looking. All without the need for engineers. [1]: https://heap.io/. - Source: Hacker News / about 3 years ago
  • We (Still) Believe in Private Offices (2015)
    Author here, surprising to see this blog post of mine trending, but it has held up pretty well! Happy to answer any questions about my time at Stack Overflow. I've since moved on to Heap (https://heap.io/) and we are hiring. We're virtual first so we don't have private offices, but we have the same values about treating developers well and giving them the space they need to do deep work. We're hiring for basically... - Source: Hacker News / over 3 years ago
View more

What are some alternatives?

When comparing Apache Spark and Heap, 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.

Google Analytics - Improve your website to increase conversions, improve the user experience, and make more money using Google Analytics. Measure, understand and quantify engagement on your site with customized and in-depth reports.

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

Adobe Analytics - Adobe Analytics is an industry-leading solution that empowers you to understand your customers as people and steer your business with customer intelligence.

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

Mixpanel - Mixpanel is the most advanced analytics platform in the world for mobile & web.

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