Software Alternatives, Accelerators & Startups

Novu VS Dagster

Compare Novu VS Dagster and see what are their differences

Novu logo Novu

The ultimate library for managing multi-channel transactional notifications with a single API.

Dagster logo Dagster

The cloud-native open source orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability.
  • Novu Landing page
    Landing page //
    2023-09-19
  • Dagster Landing page
    Landing page //
    2023-03-22

Novu videos

Lunch At Novu Pan Asian Cuisine Lahore | Food Review | Waste of money or worth going ???

More videos:

  • Review - Novu Anodized Aluminum Wireless Bluetooth Headphones ACO FULL REVIEW
  • Review - Chinese Hot Pot in Lahore || Novu Hot Pot Review || Novu Gulberg || Cook Your Own Food Restaurant

Dagster videos

Airflow Vs. Dagster: The Full Breakdown!

More videos:

  • Review - Dagster Data Orchestration 10 min walkthrough
  • Review - Apache Airflow vs. Dagster

Category Popularity

0-100% (relative to Novu and Dagster)
Developer Tools
100 100%
0% 0
Data Integration
0 0%
100% 100
Notifications And Alerting
Analytics
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 Novu and Dagster

Novu Reviews

6 Best Notification Infrastructure for Modern Applications
Novu includes a management dashboard and a centralized place to deliver real-time updates to the developers and enhance notification delivery. Being an open-source technology, Novu is free to use and offers better security and transparency than its counterparts.
Source: geekflare.com

Dagster Reviews

5 Airflow Alternatives for Data Orchestration
Dagster is an open-source data orchestration system that allows users to define their data assets as Python functions. Once defined, Dagster manages and executes these functions based on a user-defined schedule or in response to specific events. Dagster can be used at every stage of the data development lifecycle, from local development and unit testing to integration...
Top 8 Apache Airflow Alternatives in 2024
Unlike Airflow, which supports any production environment, Dagster concentrates on cloud services and supports modern data stacks. Being cloud-native and container-native, this solution makes the scheduling and execution processes easier. Dagster was created with such specific goals in mind: designing ETL data pipelines, implementing machine learning curves, and managing...
Source: blog.skyvia.com
10 Best Airflow Alternatives for 2024
Dagster is a Machine Learning, Analytics, and ETL Data Orchestrator. Since it handles the basic function of scheduling, effectively ordering, and monitoring computations, Dagster can be used as an alternative or replacement for Airflow (and other classic workflow engines).
Source: hevodata.com

Social recommendations and mentions

Based on our record, Novu should be more popular than Dagster. It has been mentiond 12 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.

Novu mentions (12)

View more

Dagster mentions (3)

What are some alternatives?

When comparing Novu and Dagster, you can also consider the following products

Courier - Courier is a notification API built for developers. Design once, and deliver to any channel – email, Slack, SMS, push, and more – all through a single API.

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

Knock App - Power your product notifications with Segment and Hightouch.

Kestra.io - Infinitely scalable, event-driven, language-agnostic orchestration and scheduling platform to manage millions of workflows declaratively in code.

SuprSend - Single Notification API for Every Channel (SMS, Slack, Whatsapp, Email, SMS, Push, App Inbox)

Prefect.io - Prefect offers modern workflow orchestration tools for building, observing & reacting to data pipelines efficiently.