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Mikro orm VS Apache Storm

Compare Mikro orm VS Apache Storm and see what are their differences

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Mikro orm logo Mikro orm

TypeScript ORM for Node.js based on Data Mapper, Unit of Work and Identity Map patterns.

Apache Storm logo Apache Storm

Apache Storm is a free and open source distributed realtime computation system.
  • Mikro orm Landing page
    Landing page //
    2021-09-10
  • Apache Storm Landing page
    Landing page //
    2019-03-11

Mikro orm features and specs

  • TypeScript Support
    MikroORM provides first-class TypeScript support, which ensures type safety and better tooling support for developers using TypeScript in their applications.
  • Supports Multiple Databases
    It is compatible with several relational databases like MySQL, PostgreSQL, SQLite, and even NoSQL databases like MongoDB, allowing flexible database management.
  • Lightweight and Efficient
    Designed to be lightweight, MikroORM offers efficient query performance and lower memory overhead compared to some heavier ORMs.
  • Active Community and Documentation
    MikroORM's documentation is comprehensive and the community is active, which makes it easier for developers to find help and resources.
  • Entity Management
    MikroORM allows powerful entity management, including features like lifecycle hooks, auto-flushing, and fully typed data models.

Possible disadvantages of Mikro orm

  • Complexity for Beginners
    New developers might find MikroORM complex compared to simpler solutions like Sequelize, particularly due to its rich feature set and TypeScript integration.
  • Learning Curve
    The learning curve can be steep for those unfamiliar with TypeScript or ORM concepts since it requires understanding both to use effectively.
  • Less Mature than Some Alternatives
    Being a relatively newer ORM, it may lack some of the battle-tested features and stability found in more established ORMs like TypeORM or Sequelize.
  • Limited Advanced Features
    MikroORM might not support certain advanced use-cases or specific database features out-of-the-box, potentially requiring custom solutions.

Apache Storm features and specs

  • Real-Time Processing
    Apache Storm is designed for processing data in real-time, which makes it ideal for applications like fraud detection, recommendation systems, and monitoring tools.
  • Scalability
    Storm is capable of scaling horizontally, allowing it to handle increasing amounts of data by adding more nodes, making it suitable for large-scale applications.
  • Fault Tolerance
    Storm provides robust fault-tolerance mechanisms by rerouting tasks from failed nodes to operational ones, ensuring continuous processing.
  • Broad Language Support
    Apache Storm supports multiple programming languages, including Java, Python, and Ruby, allowing developers to use the language they are most comfortable with.
  • Open Source Community
    Being an Apache project, Storm benefits from a strong open-source community, which contributes to its development and offers abundant resources and support.

Possible disadvantages of Apache Storm

  • Complex Setup
    Setting up and configuring Apache Storm can be complex and time-consuming, requiring detailed knowledge of its architecture and the underlying infrastructure.
  • High Learning Curve
    The architecture and components of Storm can be difficult for new users to grasp, leading to a steeper learning curve compared to some other streaming platforms.
  • Maintenance Overhead
    Managing and maintaining a Storm cluster can require significant effort, including monitoring, troubleshooting, and scaling the infrastructure.
  • Error Handling
    While Storm is fault-tolerant, its error handling at the application level can sometimes be challenging, requiring careful design to manage failures effectively.
  • Resource Intensive
    Storm can be resource-intensive, particularly in terms of memory and CPU usage, which can lead to increased costs and necessitate powerful hardware.

Mikro orm videos

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Apache Storm videos

Apache Storm Tutorial For Beginners | Apache Storm Training | Apache Storm Example | Edureka

More videos:

  • Review - Developing Java Streaming Applications with Apache Storm
  • Review - Atom Text Editor Option - Real-Time Analytics with Apache Storm

Category Popularity

0-100% (relative to Mikro orm and Apache Storm)
Development
100 100%
0% 0
Big Data
0 0%
100% 100
Web Frameworks
100 100%
0% 0
Stream Processing
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 Mikro orm and Apache Storm

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Apache Storm Reviews

Top 15 Kafka Alternatives Popular In 2021
Apache Storm is a recognized, distributed, open-source real-time computational system. It is free, simple to use, and helps in easily and accurately processing multiple data streams in real-time. Because of its simplicity, it can be utilized with any programming language and that is one reason it is a developerโ€™s preferred choice. It is fast, scalable, and integrates well...
5 Best-Performing Tools that Build Real-Time Data Pipeline
Apache Storm is an open-source distributed real-time computational system for processing data streams. Similar to what Hadoop does for batch processing, Apache Storm does for unbounded streams of data in a reliable manner. Built by Twitter, Apache Storm specifically aims at the transformation of data streams. Storm has many use cases like real-time analytics, online machine...

Social recommendations and mentions

Based on our record, Mikro orm should be more popular than Apache Storm. It has been mentiond 27 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.

Mikro orm mentions (27)

  • JavaScript Awesome Package
    Mikro-orm - TypeScript ORM for Node.js based on Data Mapper. - Source: dev.to / 5 months ago
  • Show HN: DBOS TypeScript โ€“ Lightweight Durable Execution Built on Postgres
    Why typeorm over something like https://mikro-orm.io/? - Source: Hacker News / over 1 year ago
  • Rust GraphQL APIs for NodeJS Developers: Introduction
    In my usual NodeJS tech stack, which includes GraphQL, NestJS, SQL (predominantly PostgreSQL with MikroORM), I encountered these limitations. To overcome them, I've developed a new stack utilizing Rust, which still offers some ease of development:. - Source: dev.to / over 2 years ago
  • Top 6 ORMs for Modern Node.js App Development
    Mikro-ORM is a TypeScript ORM that focuses on simplicity and efficiency. It supports various SQL databases and MongoDB. Mikro-ORM is known for its simplicity and developer-friendly APIs. It provides a concise syntax for defining data models and relationships, making it easy to use. - Source: dev.to / almost 3 years ago
  • We migrated to SQL. Our biggest learning? Don't use Prisma
    I found MikroORM [0] to be quite reasonable if you're in the TS ecosystem already. It was also easy to do custom, raw queries, and really just felt like it wasn't in the way. [0] https://mikro-orm.io/. - Source: Hacker News / almost 3 years ago
View more

Apache Storm mentions (11)

  • Data Engineering and DataOps: A Beginner's Guide to Building Data Solutions and Solving Real-World Challenges
    There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 3 years ago
  • Real Time Data Infra Stack
    Although this article lists a lot of targets for technical selection, there are definitely others that I haven't listed, which may be either outdated, less-used options such as Apache Storm or out of my radar from the beginning, like JAVA ecosystem. - Source: dev.to / over 3 years ago
  • In One Minute : Hadoop
    Storm, a system for real-time and stream processing. - Source: dev.to / over 3 years ago
  • Elon Musk reportedly wants to fire 75% of Twitterโ€™s employees
    Google has scaled well and has helped others scale, Twitter has always been behind by years. I think the only thing they did well was Twitter Storm, now taken up by Apache Foundation. Source: over 3 years ago
  • Spark for beginners - and you
    Streaming: Sparks Streamings's latency is at least 500ms, since it operates on micro-batches of records, instead of processing one record at a time. Native streaming tools like Storm, Apex or Flink might be better for low-latency applications. - Source: dev.to / over 4 years ago
View more

What are some alternatives?

When comparing Mikro orm and Apache Storm, you can also consider the following products

Beego - Beego Web is official blog and documentation website for beego app web framework

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

Propel ORM - Application and Data, Languages & Frameworks, and Microframeworks (Backend)

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

Hibernate - Hibernate an open source Java persistence framework project.

Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.