Software Alternatives, Accelerators & Startups

Apache Spark VS Flatlogic

Compare Apache Spark VS Flatlogic 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.

Flatlogic logo Flatlogic

AI-Powered Software Development for Startups and Businesses
  • Apache Spark Landing page
    Landing page //
    2021-12-31
Not present

Flatlogic specializes in building web-based business software and applications using AI and innovative technologies. Our platform, Flatlogic Generator, allows users to create custom SaaS, ERP, CRM, CMS, and other solutions quickly and efficiently, offering full code ownership and scalability. With a focus on enterprise applications, we help businesses save time and resources while delivering robust and customizable solutions. Contact us for software development, integration, and customization services.

Flatlogic

$ Details
freemium $20.0 / Monthly
Release Date
2022 October
Startup details
Country
Poland
City
Warsaw
Employees
20 - 49

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.

Flatlogic features and specs

  • Streamlined Development
    Flatlogic provides pre-built application templates that can significantly speed up the development process by reducing the need for manual coding.
  • Customization Options
    Offers various templates and layouts that can be customized to fit specific project requirements, providing flexibility for developers.
  • Modern Technologies
    Flatlogic uses modern technologies such as React, Angular, and Vue, making it easier to integrate with current software ecosystems.
  • Comprehensive Documentation
    Documentation is thorough, making it easier for developers to understand how to use the platform and get up and running quickly.
  • Responsive Design
    Templates are designed to be fully responsive, ensuring applications look good on both desktop and mobile devices.
  • User Support
    Provides good customer support, including options for live chat and ticketing, helping users resolve issues quickly.

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 Flatlogic

Overall verdict

  • Overall, Flatlogic is considered a good choice for developers who need to expedite the web application development process without compromising quality. It caters to both beginners with its straightforward templates and experienced developers who can utilize its more advanced features.

Why this product is good

  • Flatlogic (flatlogic.com) is regarded as a useful platform for developers and businesses looking to create web applications quickly and efficiently. It offers a wide range of pre-built templates, starter kits, and full-stack web application generators that help in cutting down development time and focusing more on customizing the app to meet specific needs. Users appreciate the ease of use, comprehensive documentation, and the time saved in setting up the infrastructure from scratch.

Recommended for

    Flatlogic is recommended for startups, small to medium-sized businesses, and independent developers who want to accelerate the development of web applications. It's particularly beneficial for teams that need to launch projects quickly, those who have limited resources for building from scratch, and for educators or learners interested in understanding the structure of modern web applications.

Apache Spark videos

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

Flatlogic videos

AI-Driven Business Software - Flatlogic App Generator

Category Popularity

0-100% (relative to Apache Spark and Flatlogic)
Databases
100 100%
0% 0
Developer Tools
0 0%
100% 100
Big Data
100 100%
0% 0
Design Tools
0 0%
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 Flatlogic

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...
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...
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...

Flatlogic Reviews

We have no reviews of Flatlogic yet.
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Social recommendations and mentions

Based on our record, Apache Spark should be more popular than Flatlogic. 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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Flatlogic mentions (16)

  • AI Software Development: Trends for the Next 5 Years
    Work with Flatlogic, and step into the future of the next-generation AI software development today! - Source: dev.to / 3 months ago
  • Why Custom ERP is the Best Fit for Scaling Businesses
    So, why choose a system that only half-serves your business? Take control of your business operations today. Start building your custom ERP with Flatlogic’s code generator now! - Source: dev.to / 3 months ago
  • Best SAP Alternatives 2025: Choose the Right ERP
    Choose Flatlogic if you want to build a smart and effective ERP system that ensures agility and helps your business easily adapt in a fast-pressurized modern world. - Source: dev.to / 3 months ago
  • AI Web App Generators: Build in Minutes
    Of the AI web app generators listed, Flatlogic stands out with its customizable database schema, comprehensive authentication, and full-stack capabilities. Start building your dream app today with Flatlogic’s code generator. - Source: dev.to / 4 months ago
  • Best 10+ Open Source CRM Systems
    Tailored to the intricate needs of modern businesses, Flatlogic Custom CRM stands out by providing a CRM solution that isn’t just flexible — it’s entirely moldable to your business needs. Designed to serve as the backbone for customer relationship management, Flatlogic Custom CRM emerges from a powerful lineage of business software development, integrating seamlessly into various industries’ workflows. The system... - Source: dev.to / 11 months ago
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What are some alternatives?

When comparing Apache Spark and Flatlogic, 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.

ArchitectUI - Modern dashboard template for bootstrap 4

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

DesignRevision - Powerful tools for web professionals

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

Soft UI Dashboard - Admin dashboard template for Bootstrap 5