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Vultr VS Apache Spark

Compare Vultr VS Apache Spark and see what are their differences

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Vultr logo Vultr

VULTR Global Cloud Hosting - Brilliantly Fast SSD VPS Cloud Servers. 100% KVM Virtualization

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.
  • Vultr Landing page
    Landing page //
    2022-10-07
  • Apache Spark Landing page
    Landing page //
    2021-12-31

Vultr features and specs

  • Global Data Centers
    Vultr offers numerous data centers worldwide, enabling users to host their services closer to their target audience, which can improve speed and reliability.
  • Scalability
    Vultr enables seamless scaling of resources, allowing users to start modestly and upgrade as their needs grow without significant downtime.
  • Competitive Pricing
    Vultr provides competitively priced plans, including affordable entry-level options, making it accessible for small businesses and startups.
  • High Performance
    With SSD-based storage and high-performance networking, Vultr offers strong performance and quick load times for applications and websites.
  • User-Friendly Interface
    The Vultr control panel is intuitive and user-friendly, enabling users to deploy and manage their instances with ease.
  • Wide Range of Services
    Vultr offers various services, including compute instances, block storage, and dedicated servers, accommodating diverse hosting needs.
  • Custom ISO Support
    Users can upload their custom ISOs, which provides greater flexibility in deploying operating systems and specialized software.

Possible disadvantages of Vultr

  • Limited Customer Support
    Vultr's customer support options may be limited as it primarily relies on ticket-based support, which can result in slower response times for urgent issues.
  • No Free Tier
    Unlike some competitors, Vultr does not offer a free tier, which could be a deterrent for developers looking to test the platform without incurring costs.
  • Complex Pricing Structure
    Customers may find Vultr's pricing structure somewhat complex, especially when factoring in additional costs for features like bandwidth and snapshots.
  • Lack of Advanced Managed Services
    Vultr primarily offers unmanaged services, which may require more hands-on management and maintenance from users compared to other providers with advanced managed services.
  • Variable Performance Metrics
    Some users report variability in performance metrics, especially under high load conditions, which could affect critical applications.
  • Limited Pre-configured Options
    While Vultr provides flexibility, it has fewer pre-configured, out-of-the-box solutions for popular applications compared to its competitors.

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.

Vultr videos

+ Add

Vultr Cloud Server Review

More videos:

  • Review - SITEGROUND VS VULTR REVIEW 🤑 HONEST 💯 PROMO CODES
  • Review - Digital Ocean VS Vultr VS Linode for Don't Starve Together Dedicated Servers

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

Category Popularity

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

Vultr

Apache Spark

Cloud Computing
100 100%
Cloud Computing
0% 0
Databases
0 0%
Databases
100% 100
Cloud Infrastructure
100 100%
Cloud Infrastructure
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using Vultr and Apache Spark. For example, how are they different and which one is better?
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Reviews

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

Vultr Reviews

Best Linux VPS [Top 10 Linux VPS Provider 2024]
Like DigitalOcean, Vultr can be hard to navigate through. They offer many different VPS services that can confuse you if you need a standard Linux VPS. Their prices vary from plan to plan, but they can get as high as $14.000 a month, depending on your needs. Vultr also has a strict policy about not offering a refund guarantee. If you are looking for a basic Linux VPS, Vultr...
Source: cloudzy.com
Top 50 Cheapest Cloud Services Providers | Affordable Cloud Hosting
Vultr is a low-cost cloud hosting service that offers monthly plans starting at $2.50. Vultr’s plans are very similar to DigitalOcean’s; in fact, Vultr’s cloud plans are more affordable. The most basic plan costs $2.50 per month and includes 20GB SSD storage, 512 RAM, 1 CPU core, and 500GB bandwidth. The next package costs $5 and includes a 25GB SSD, 1 CPU, 1024 RAM, and...
Source: makeanapplike.com
13 Best Windows VPS and Cloud Hosting Platform
Vultr servers are built on Intel core CPU and got multiple locations worldwide. There is no long-term contract.
Source: geekflare.com
Best Vultr Alternatives and Competitor Cloud Services of 2022
Scaleway is another well reputed Vultr competitor that offers cloud based solutions such as virtual instances, GPU instances, Bare metal cloud servers, Kubernetes Kapsule, and various block storage services. Similar to Vultr pricing, they also have cheaper prices as well as the best money value packages. Some large enterprises like Adobe, Dailymotion, Safran, Seloger, and...
Source: www.mytipshub.com
Top 10+ Alternatives to DigitalOcean
Vultr is another DigitalOcean alternative that provides its cloud computing services with high-performance cloud servers. Vultr provides cloud computing services with its powerful control panel and APIs.
Source: blog.back4app.com

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

Social recommendations and mentions

Apache Spark might be a bit more popular than Vultr. We know about 70 links to it since March 2021 and only 58 links to Vultr. 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.

Vultr mentions (58)

  • Switching from Squarespace to WooCommerce. Not a dev.
    Vultr.com pick the $5 monthly plan and enable backup. Source: over 1 year ago
  • Recommendation request - no transfer limit and allows custom images, <=$10/mo
    Most reputable places out there will allow everything above (and match your budget), such as Linode, or Vultr (there are others). Source: over 1 year ago
  • Lamp Stack website
    I recommend Hetzner or Vultr as a VPS provider as they're cheap and I/my friends have had good experiences with them. Source: over 1 year ago
  • VPS servers
    Am I allowed to use VPS servers from vultr to use honeygain. Source: almost 2 years ago
  • Unlimited bandwidth vps cloud service in India?
    Linode (Mumbai) and DigitalOcean (Bangalore) each have a single DC in India, and Vultr has 3 (Mumbai, Bangalore, Delhi). Source: about 2 years ago
View more

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 1 month 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 / 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 / 3 months ago
View more

What are some alternatives?

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

DigitalOcean - Simplifying cloud hosting. Deploy an SSD cloud server in 55 seconds.

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

Linode - We make it simple to develop, deploy, and scale cloud infrastructure at the best price-to-performance ratio in the market.

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

Amazon AWS - Amazon Web Services offers reliable, scalable, and inexpensive cloud computing services. Free to join, pay only for what you use.

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

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