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OutSystems VS Apache Spark

Compare OutSystems VS Apache Spark and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

OutSystems logo OutSystems

Build Enterprise-Grade Apps Fast.

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.
  • OutSystems Landing page
    Landing page //
    2023-05-10
  • Apache Spark Landing page
    Landing page //
    2021-12-31

OutSystems

Website
outsystems.com
Pricing URL
Official OutSystems Pricing
$ Details
-
Release Date
2001 January
Startup details
Country
United States
State
Massachusetts
City
Boston
Founder(s)
Paulo Rosado
Employees
1,000 - 1,999
Edit details

Apache Spark

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

OutSystems features and specs

  • Speed of Development
    OutSystems offers rapid application development through its low-code platform, allowing developers to build apps much faster than traditional coding approaches.
  • Integration Capabilities
    The platform supports easy integration with existing systems, databases, and a wide range of third-party services, making it versatile for various business environments.
  • Scalability
    OutSystems provides scalable architecture, enabling applications built on the platform to grow and handle increasing loads efficiently.
  • Cross-Platform Deployment
    OutSystems allows for seamless deployment across multiple platforms, including web, mobile, and desktop, from a single codebase.
  • User Experience (UX) & UI Components
    The platform offers a wide range of pre-built UI components and templates, which helps in creating visually appealing and user-friendly applications.
  • Strong Community and Support
    OutSystems has an active community of developers and offers extensive documentation and support, aiding in problem-solving and learning.
  • Security
    OutSystems emphasizes security, providing built-in features like role-based access control, audit logs, and encryption, ensuring that applications are secure.

Possible disadvantages of OutSystems

  • Cost
    OutSystems can be expensive, especially for smaller businesses or startups due to its pricing structure, which may restrict its accessibility.
  • Learning Curve
    Although it is a low-code platform, mastering OutSystems requires a certain amount of learning and adaptation, especially for developers used to traditional coding.
  • Vendor Lock-In
    Applications built on OutSystems are tightly coupled with the platform, which can make it difficult to migrate to other solutions if needed.
  • Complex Custom Requirements
    While OutSystems is highly flexible, certain complex custom functionalities might still require traditional coding or workarounds, which can increase development time.
  • Performance
    For highly complex or performance-sensitive applications, the abstraction provided by a low-code platform like OutSystems can sometimes lead to suboptimal performance.
  • Limited Offline Capabilities
    Offline capabilities are somewhat limited compared to fully native development options, potentially restricting the use cases for certain types of mobile applications.
  • Dependency on Proprietary Tools
    Relying on OutSystems means depending on proprietary tools and services, which could be a disadvantage if the company decides to change its toolset or strategy.

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.

Analysis of OutSystems

Overall verdict

  • Overall, OutSystems is considered a good choice for organizations looking to streamline their application development process, allowing them to focus on business logic and user experience rather than technical complexities. Its powerful features and ease of use make it an attractive option in the low-code development market.

Why this product is good

  • OutSystems is widely regarded as a robust low-code application development platform that facilitates faster application delivery. It allows businesses to rapidly develop, deploy, and manage apps with minimal hand-coding, making it accessible for organizations that need to build applications quickly but may not have extensive technical resources. Additionally, the platform offers seamless integration capabilities, scalability, and a wide range of pre-built templates and components that accelerate the development process.

Recommended for

  • Businesses seeking rapid development and deployment of applications.
  • Organizations with limited technical resources or looking to minimize hand-coding.
  • Companies needing scalable solutions that can evolve with their business needs.
  • Teams that require seamless integration with existing systems and third-party services.
  • Enterprises looking for a versatile platform that can be used to build both web and mobile applications.

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.

OutSystems videos

+ Add

Outsystems: Low-Code Apps - This Week in Enterprise Tech 317

More videos:

  • Review - OutSystems Overview

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 OutSystems and Apache Spark)

OutSystems

Apache Spark

Developer Tools
100 100%
Developer Tools
0% 0
Databases
0 0%
Databases
100% 100
Project Management
100 100%
Project Management
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using OutSystems 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 OutSystems and Apache Spark

OutSystems Reviews

Low-Code Platforms Compared: Enterprise Guide for Developers
OutSystems: Strong enterprise governance, lifecycle tooling, and AI-assisted development, with newer agent capabilities through Agent Workbench. Good fit for governed app delivery, but less suited to cross-system orchestration.
Source: rierino.com
Top 10 Microsoft Power Apps Alternatives and Competitors 2024
Strengths: This established low-code platform delivers rapid application development with a focus on scalability and security. OutSystems offers a mature platform ideal for building mission-critical enterprise applications. It boasts strong features for API management, integration with various data sources, and cloud deployment options.
Source: medium.com
THE BEST 34 APP DEVELOPMENT SOFTWARE IN 2022 LIST
Development With No Limits. Everything you need to build enterprise apps incredibly fast. Every aspect of OutSystems is crafted to help you build better apps faster and make changes easily. From high-productivity visual development to powerful tools to deploy and manage your apps. Key features include:
Source: www.edigitalagency.com.au
Android Studio Alternative
OutSystems is a low-code platform that allows businesses to create, deploy, and manage multichannel enterprise apps. You can handle your application backlog, offer cloud-based contemporary apps, and stay up with changing company needs to promote future innovation with OutSystems. OutSystems is a modern application platform that allows you to substantially accelerate the...
Source: www.educba.com
10 Best Low-Code Development Platforms in 2020
OutSystems provides the platform for developers to easily deliver and edit those applications. Salesforce Lightning is a suite of tools for developing business apps. Zoho Creator low code development platform can be used by non-developers and is perfect for building simple applications.
Source: www.softwaretestinghelp.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 โ€“ 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

Based on our record, Apache Spark seems to be a lot more popular than OutSystems. While we know about 80 links to Apache Spark, we've tracked only 2 mentions of OutSystems. 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.

OutSystems mentions (2)

  • How I became low-code certified with OutSystems
    This month, I followed in the footsteps of many other OutSystems developers and completed the exam to become a certified Associate Reactive Developer. This exam focuses on the fundamentals of OutSystems reactive web and mobile application development, and is for developers new to the OutSystems platform. - Source: dev.to / over 2 years ago
  • OutSystems Dynamic Request Routing in Multi-tenant Systems with Amazon CloudFront
    Check out the AWS Architecture Blog to see how OutSystems designed a globally distributed serverless request routing service for its multi-tenant architecture. Source: over 5 years ago

Apache Spark mentions (80)

  • MLOps Lifecycle: Stages, Workflow, and Best Practices
    Feature transformations should be deterministic: The same input should produce the same output when the same feature definition and configuration are applied. This is what allows training, backtesting, and live inference to remain aligned. Tools such as Pandas, Spark, or feature platforms such as Feast can be used to implement that logic. - Source: dev.to / 2 months ago
  • 7 Free Tools for Data Pipeline Reconciliation and Cross-Source Validation
    Apache Spark provides distributed in-memory data processing and is the appropriate tool when the data set to be reconciled does not fit in a single machine's memory, or when parallelizing the comparison across a cluster would reduce runtime from hours to minutes. - Source: dev.to / 3 months ago
  • Why Apache IoTDB Is Written in Java: A Decade of Engineering Trade-offs
    When IoTDB was initiated in 2011, almost all influential distributed systems and databases were built in Java or on the JVMโ€”such as Hadoop, HBase, Spark (Scala on JVM), Cassandra, Kafka, and Flink. To integrate deeply with the big data ecosystem, choosing Java was a natural decision. - Source: dev.to / 5 months ago
  • I Scraped 47M+ Hacker News Items Into Parquet Files โ€“ Here's What I Discovered About HN's Hidden Data Patterns
    For handling even larger datasets or building production applications, Apache Spark provides excellent Parquet support with distributed processing capabilities. - Source: dev.to / 5 months ago
  • Show HN: Spark โ€“ Zero-config IoT deployment tool written in Rust
    You may want to consider renaming this project. The name "Spark" already refers to: A popular data analytics framework of the Apache Foundation: https://spark.apache.org/ A subset of the Ada programming language used for formal verification: https://learn.adacore.com/courses/intro-to-spark/chapters/01_Overview.html An Nvidia AI development system: https://www.nvidia.com/en-us/products/workstations/dgx-spark/. - Source: Hacker News / 7 months ago
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What are some alternatives?

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

Mendix - Mendix is the fastest and easiest low-code platform used by businesses to create and continuously improve mobile and web apps at scale.

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

Zoho Creator - Zoho Creator is a low-code application development platform that helps you build a custom, mobile-ready apps to run your business.

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

Xamarin - Create iOS, Android and Mac apps in C#

Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.

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