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Flyway VS Google Cloud Dataflow

Compare Flyway VS Google Cloud Dataflow and see what are their differences

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Flyway logo Flyway

Flyway is a database migration tool.

Google Cloud Dataflow logo Google Cloud Dataflow

Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
  • Flyway Landing page
    Landing page //
    2023-08-02
  • Google Cloud Dataflow Landing page
    Landing page //
    2023-10-03

Flyway features and specs

  • Database Versioning
    Flyway provides robust version control for your database schemas, which ensures that all changes are tracked and can be rolled back if necessary.
  • Ease of Use
    Easy to set up and use, Flyway supports several databases and integrates seamlessly with CI/CD pipelines, making it a versatile tool.
  • Script-based Migrations
    Allows for migration scripts to be written in SQL or Java, offering flexibility in how schema changes are implemented.
  • Idempotence
    Ensures that migration scripts are idempotent, meaning that they can be applied multiple times without causing conflicts or errors, which is vital for predictable deployments.
  • Tool Integration
    Integrates well with various build tools and frameworks like Maven, Gradle, and Spring Boot, enhancing its utility across different environments.
  • Community and Support
    Large and active community along with comprehensive documentation and commercial support options, helping users resolve issues efficiently.

Possible disadvantages of Flyway

  • Learning Curve
    New users might experience a learning curve understanding all of its features, configurations, and best practices.
  • Limited Undo Functionality
    Flyway doesn't natively support down migrations (rollbacks); this has to be implemented manually, increasing the workload on developers.
  • Initial Setup Overhead
    Requires some initial setup and configuration which might be cumbersome for small projects or one-off databases.
  • No Schema Diffing
    Unlike some other tools, Flyway does not natively support schema diffing (the ability to generate change scripts from schema differences), so developers need to write every change explicitly.
  • Dependency Management
    Managing dependencies for Flyway scripts can become complex, particularly in larger projects, as it requires careful coordination across development teams.
  • License Cost
    While Flyway offers a free version, some advanced features are locked behind a paid version, which could be a constraint for some organizations.

Google Cloud Dataflow features and specs

  • Scalability
    Google Cloud Dataflow can automatically scale up or down depending on your data processing needs, handling massive datasets with ease.
  • Fully Managed
    Dataflow is a fully managed service, which means you don't have to worry about managing the underlying infrastructure.
  • Unified Programming Model
    It provides a single programming model for both batch and streaming data processing using Apache Beam, simplifying the development process.
  • Integration
    Seamlessly integrates with other Google Cloud services like BigQuery, Cloud Storage, and Bigtable.
  • Real-time Analytics
    Supports real-time data processing, enabling quicker insights and facilitating faster decision-making.
  • Cost Efficiency
    Pay-as-you-go pricing model ensures you only pay for resources you actually use, which can be cost-effective.
  • Global Availability
    Cloud Dataflow is available globally, which allows for regionalized data processing.
  • Fault Tolerance
    Built-in fault tolerance mechanisms help ensure uninterrupted data processing.

Possible disadvantages of Google Cloud Dataflow

  • Steep Learning Curve
    The complexity of using Apache Beam and understanding its model can be challenging for beginners.
  • Debugging Difficulties
    Debugging data processing pipelines can be complex and time-consuming, especially for large-scale data flows.
  • Cost Management
    While it can be cost-efficient, the costs can rise quickly if not monitored properly, particularly with real-time data processing.
  • Vendor Lock-in
    Using Google Cloud Dataflow can lead to vendor lock-in, making it challenging to migrate to another cloud provider.
  • Limited Support for Non-Google Services
    While it integrates well within Google Cloud, support for non-Google services may not be as robust.
  • Latency
    There can be some latency in data processing, especially when dealing with high volumes of data.
  • Complexity in Pipeline Design
    Designing pipelines to be efficient and cost-effective can be complex, requiring significant expertise.

Analysis of Flyway

Overall verdict

  • Overall, Flyway is a robust and efficient tool for database version control and migrations, praised for its simplicity and effectiveness in managing database changes across different environments.

Why this product is good

  • Flyway (flywaydb.org) is considered good because it simplifies the process of managing database migrations by providing a structured and version-controlled way to handle schema changes. It supports a wide range of databases and offers both command-line and API access, making it versatile for different development workflows. Additionally, Flyway's migration scripts are executed in a consistent manner, ensuring database integrity and reducing the risk of errors during deployments.

Recommended for

    Flyway is recommended for developers and teams looking for a straightforward solution to manage database migrations, especially in agile and continuous integration/continuous deployment (CI/CD) environments. It is particularly useful for teams that need to ensure database consistency across different stages of development and production.

Analysis of Google Cloud Dataflow

Overall verdict

  • Google Cloud Dataflow is a strong choice for users who need a flexible and scalable data processing solution. It is particularly well-suited for real-time and large-scale data processing tasks. However, the best choice ultimately depends on your specific requirements, including cost considerations, existing infrastructure, and technical skills.

Why this product is good

  • Google Cloud Dataflow is a fully managed service for stream and batch data processing. It is based on the Apache Beam model, allowing for a unified data processing approach. It is highly scalable, offers robust integration with other Google Cloud services, and provides powerful data processing capabilities. Its serverless nature means that users do not have to worry about infrastructure management, and it dynamically allocates resources based on the data processing needs.

Recommended for

  • Organizations that require real-time data processing.
  • Projects involving complex data transformations.
  • Users who already utilize Google Cloud Platform and need seamless integration with other Google services.
  • Developers and data engineers familiar with Apache Beam or those willing to learn.

Flyway videos

+ Add

Flyway Review: Echo XLT Duck Call

More videos:

  • Review - Flyway Review: Echo Timber Duck Call
  • Review - Beer Review # 3455 Flyway Brewing Early Bird IPA

Google Cloud Dataflow videos

+ Add

Introduction to Google Cloud Dataflow - Course Introduction

More videos:

  • Review - Serverless data processing with Google Cloud Dataflow (Google Cloud Next '17)
  • Review - Apache Beam and Google Cloud Dataflow

Category Popularity

0-100% (relative to Flyway and Google Cloud Dataflow)

Flyway

Google Cloud Dataflow

MySQL Tools
100 100%
MySQL Tools
0% 0
Big Data
0 0%
Big Data
100% 100
Online Services
100 100%
Online Services
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100

User comments

Share your experience with using Flyway and Google Cloud Dataflow. 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 Flyway and Google Cloud Dataflow

Flyway Reviews

We have no reviews of Flyway yet.
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Google Cloud Dataflow Reviews

Top 8 Apache Airflow Alternatives in 2024
Google Cloud Dataflow is highly focused on real-time streaming data and batch data processing from web resources, IoT devices, etc. Data gets cleansed and filtered as Dataflow implements Apache Beam to simplify large-scale data processing. Such prepared data is ready for analysis for Google BigQuery or other analytics tools for prediction, personalization, and other purposes.
Source: blog.skyvia.com

Social recommendations and mentions

Based on our record, Flyway should be more popular than Google Cloud Dataflow. It has been mentiond 61 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.

Flyway mentions (61)

  • Best Database Migration Tools for Golang
    Flyway is a Java-based migration tool that’s widely used in enterprise settings. While not Go-native, you can integrate it into Go projects using its CLI or by calling its Java library. Flyway is great for teams needing robust versioning and audit-ready migration history. - Source: dev.to / 4 days ago
  • Run Flyway DB migrations with AWS Lambda and RDS - Part 1
    Usually there is a need to run SQL database updates: update table columns, add new rows, create a new schema etc. Often developer teams are using Flyway It is an open-source database SQL deployment tool. In Flyway, all DDL and DML changes to the database are called migrations. Migrations can be versioned or repeatable. - Source: dev.to / about 1 year ago
  • A Journey Towards A Scalable Multi-Tenant Application
    Our client's engineering team recommended Flyway and successfully used it to manage their migrations. We chose to adopt Flyway due to its simplicity, speed, reliability, and successful implementation by our client's engineering team. Their existing codebase and experiences allowed us to transition smoothly to Flyway. - Source: dev.to / 12 months ago
  • Let's write a simple microservice in Clojure
    The session logs show that the application loads configurations and establishes a connection with a PostgreSQL database. This involves initializing a HikariCP connection pool and Flyway for database migrations. The logs confirm that the database schema validation and migration checks were successful. The startup of the Jetty HTTP server follows, and the server becomes operational and ready to accept requests on... - Source: dev.to / about 1 year ago
  • Ask HN: What tool(s) do you use to code review and deploy SQL scripts?
    Also RedGate, but Flyway has some reasons to recommend it over RedGate Deploy depending on your DBAs/workflows: https://flywaydb.org/ (Though I don't think it is "complete" or "perfect", either.) EF Migrations are in a really good place now if you like/don't mind C# as a language (and you can easily embed SQL inside the C#, too, but there are benefits to being able to also run high level C# code). With today's... - Source: Hacker News / about 1 year ago
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Google Cloud Dataflow mentions (14)

  • How do you implement CDC in your organization
    Imo if you are using the cloud and not doing anything particularly fancy the native tooling is good enough. For AWS that is DMS (for RDBMS) and Kinesis/Lamba (for streams). Google has Data Fusion and Dataflow . Azure hasData Factory if you are unfortunate enough to have to use SQL Server or Azure. Imo the vendored tools and open source tools are more useful when you need to ingest data from SaaS platforms, and... Source: over 2 years ago
  • Here’s a playlist of 7 hours of music I use to focus when I’m coding/developing. Post yours as well if you also have one!
    This sub is for Apache Beam and Google Cloud Dataflow as the sidebar suggests. Source: over 2 years ago
  • How are view/listen counts rolled up on something like Spotify/YouTube?
    I am pretty sure they are using pub/sub with probably a Dataflow pipeline to process all that data. Source: over 2 years ago
  • Best way to export several GCP datasets to AWS?
    You can run a Dataflow job that copies the data directly from BQ into S3, though you'll have to run a job per table. This can be somewhat expensive to do. Source: over 2 years ago
  • Why we don’t use Spark
    It was clear we needed something that was built specifically for our big-data SaaS requirements. Dataflow was our first idea, as the service is fully managed, highly scalable, fairly reliable and has a unified model for streaming & batch workloads. Sadly, the cost of this service was quite large. Secondly, at that moment in time, the service only accepted Java implementations, of which we had little knowledge... - Source: dev.to / about 3 years ago
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What are some alternatives?

When comparing Flyway and Google Cloud Dataflow, you can also consider the following products

Liquibase - Database schema change management and release automation solution.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Slick - A jquery plugin for creating slideshows and carousels into your webpage.

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

Sequel Pro - MySQL database management for Mac OS X

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

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