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Apache Spark for Azure HDInsight VS Snowplow

Compare Apache Spark for Azure HDInsight VS Snowplow and see what are their differences

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Apache Spark for Azure HDInsight logo Apache Spark for Azure HDInsight

This article provides an introduction to Spark in HDInsight and the different scenarios in which you can use Spark cluster in HDInsight.

Snowplow logo Snowplow

Snowplow is an enterprise-strength event analytics platform.
  • Apache Spark for Azure HDInsight Landing page
    Landing page //
    2023-03-17
  • Snowplow Landing page
    Landing page //
    2023-10-05

Our Mission is to empower data teams to build a strategic data capability that delivers high-quality, complete, and relevant data across the business. Our users and customers use Snowplow for numerous use cases – from web and mobile analytics to advanced analytics and the production of AI & ML ready data, whilst maintaining data privacy compliance. Our customers reflect the diversity of use cases that Snowplow solves and includes Strava, The Wall Street Journal, CapitalOne, WeTransfer, Nordstrom, DataDog, Auto Trader, GitLab and many more.

Apache Spark for Azure HDInsight features and specs

  • Scalability
    Apache Spark on Azure HDInsight can easily scale to handle large datasets by distributing data across multiple nodes, making it suitable for big data processing.
  • Integration with other Azure Services
    Apache Spark on Azure HDInsight seamlessly integrates with other Azure services like Azure Blob Storage, Azure SQL Database, and Power BI, enhancing its capabilities within the Azure ecosystem.
  • Real-time Data Processing
    Spark supports real-time data analytics, enabling faster processing using features such as Spark Streaming to handle data as it arrives.
  • Ease of Use
    HDInsight's managed Spark service simplifies cluster creation, configuration, and management, allowing users to focus more on data analysis rather than infrastructure.
  • Support for Multiple Languages
    Spark supports various programming languages such as Scala, Java, Python, and R, providing flexibility in how users can write their processing logic.

Possible disadvantages of Apache Spark for Azure HDInsight

  • Complexity in Tuning
    Despite its power, Spark can be complex to tune and optimize, which may require significant expertise to achieve optimal performance.
  • Cost
    Running Apache Spark on Azure HDInsight can become expensive, especially with large-scale deployments and continuous operations, requiring careful cost management.
  • Resource Management
    Efficient resource management can be challenging as Spark requires careful allocation of memory and CPU to ensure optimal job execution and performance.
  • Learning Curve
    For users new to big data technologies or the Spark ecosystem, there can be a steep learning curve associated with understanding and effectively using Spark on HDInsight.
  • Dependency on Azure
    While integration with Azure services is a pro, it also means a strong dependency on the Azure platform, which might not be ideal for organizations looking to remain cloud-agnostic.

Snowplow features and specs

  • Data Ownership
    Snowplow allows organizations to own their data end-to-end, providing more control over data collection, storage, and usage compared to third-party analytics platforms.
  • Flexibility
    The platform offers a high degree of customization, allowing businesses to track custom events and define their own data structures, which is ideal for complex or unique data needs.
  • Real-time Analytics
    Snowplow supports real-time data processing, which enables organizations to make swift, data-driven decisions and insights.
  • Open Source
    Being an open-source solution, Snowplow can be adopted without licensing costs, and there is a community for support and continuous development.
  • Cross-Platform Tracking
    Snowplow allows for tracking across multiple platforms and devices, providing a unified view of the customer journey.
  • Data Enrichment
    The solution offers capabilities to enrich event data with additional context such as geo-location or user session data, adding more value to raw data.

Possible disadvantages of Snowplow

  • Complex Setup
    Setting up Snowplow requires significant technical expertise, including infrastructure management, which may be a barrier for smaller teams or companies without specialized resources.
  • Maintenance Effort
    Ongoing maintenance and updates to the Snowplow setup can be labor-intensive, requiring continuous monitoring and management.
  • Infrastructure Costs
    While Snowplow itself is open source, the infrastructure required to run it (e.g., servers, databases, data storage) can be costly.
  • Learning Curve
    Due to its flexibility and customization options, there is a steep learning curve for new users, which may delay the onboarding process.
  • Data Privacy Responsibility
    Since organizations own their data, they are also fully responsible for compliance with data privacy regulations (e.g., GDPR), necessitating additional efforts in data governance.

Analysis of Snowplow

Overall verdict

  • Snowplow is a robust and flexible data collection platform that is well-suited for organizations looking for a customizable and scalable analytics solution. Its open-source nature and comprehensive feature set make it a strong contender in the analytics space.

Why this product is good

  • Snowplow Analytics is considered a good choice due to its ability to offer highly customizable and granular data collection, which allows businesses to gather and analyze data tailored to their specific needs. It provides real-time event tracking, offers a wide range of integration options, and supports multiple programming languages and third-party services. Additionally, it is open-source, giving users control over their data infrastructure and reducing dependency on third-party vendors.

Recommended for

    Snowplow is recommended for data-driven organizations, particularly those with technical expertise and resources to manage an open-source solution. It is suitable for businesses that require detailed tracking and analysis of customer journeys, complex data pipelines, and those seeking to integrate data across various platforms and touchpoints.

Apache Spark for Azure HDInsight videos

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What is Snowplow

Category Popularity

0-100% (relative to Apache Spark for Azure HDInsight and Snowplow)

Apache Spark for Azure HDInsight

Snowplow

Big Data
100 100%
Big Data
0% 0
Analytics
0 0%
Analytics
100% 100
Data Dashboard
37 37%
Data Dashboard
63% 63
Web Analytics
0 0%
Web Analytics
100% 100

User comments

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Social recommendations and mentions

Based on our record, Snowplow seems to be more popular. It has been mentiond 10 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 for Azure HDInsight mentions (0)

We have not tracked any mentions of Apache Spark for Azure HDInsight yet. Tracking of Apache Spark for Azure HDInsight recommendations started around Mar 2021.

Snowplow mentions (10)

  • Open-source data collection & modeling platform for product analytics
    We’ve also thought about Ops :-). There’s a backend 'Collector' that stores data in Postgres, for instance to use while developing locally, or if you want to get set up quickly. But there’s also full integration with Snowplow, which works seamlessly with an existing Snowplow setup as well. - Source: dev.to / almost 3 years ago
  • What are the different ways to collect large amounts of data, like millions of rows?
    Sure thing! Say you run an online store. Your source systems could be the inventory, orders or customer databases. You could also track click/site behavior with something like snowplow. An ERP system is essentially just a combination of what I mentioned previously. Another good example is a CRM such as Salesforce or Zendesk. Hopefully that helps! Source: about 3 years ago
  • The Big Data Game – Because even a simple query can send you on an unexpected journey. Help the 8-bit data engineer to get the data
    Well if you have to structure and create Schema and manage Data Warehouses, you need a tool to do that, so in the background you see SnowPlow, which helps you do just that. Make the data into some kind of sensible structure so that later on business analysts can come see whats up. Want to do a quarterly report on how you performed, go to the application that goes to the data warehouse and builds your report for... Source: about 3 years ago
  • Reference Data Stack for Data-Driven Startups
    We also have telemetry set up on our Monosi product which is collected through Snowplow,. As with Airbyte, we chose Snowplow because of its open source offering and because of their scalable event ingestion framework. There are other open source options to consider including Jitsu and RudderStack or closed source options like Segment. Since we started building our product with just a CLI offering, we didn’t need a... - Source: dev.to / over 3 years ago
  • Ask HN: Best alternatives to Google Analytics in 2021?
    Https://matomo.org That's the only full featured open source competitor I am aware of, so it should be mentioned. https://snowplowanalytics.com/ Somewhat FOSS. There was a story there, but I don't remember the details. - Source: Hacker News / over 3 years ago
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What are some alternatives?

When comparing Apache Spark for Azure HDInsight and Snowplow, you can also consider the following products

Snowflake - Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.

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.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Glass Analytics - Google Analytics alternative that shows you exactly how visitors become customers.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

Simple Analytics - The privacy-first Google Analytics alternative located in Europe.

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