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  1. Stackups
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  4. Big Data As A Service
  5. Amazon Redshift vs Flyway

Amazon Redshift vs Flyway

OverviewDecisionsComparisonAlternatives

Overview

Amazon Redshift
Amazon Redshift
Stacks1.5K
Followers1.4K
Votes108
Flyway
Flyway
Stacks305
Followers563
Votes33
GitHub Stars9.2K
Forks1.6K

Amazon Redshift vs Flyway: What are the differences?

Introduction

When it comes to database management, Amazon Redshift and Flyway are two popular tools that serve different purposes. Understanding the key differences between these tools can help in making informed decisions for database management.

  1. Purpose and Functionality: Amazon Redshift is a fully managed, petabyte-scale data warehouse service that allows users to analyze and query large datasets using SQL. On the other hand, Flyway is an open-source database migration tool that helps automate and manage the versioning of database schemas over time. While Redshift focuses on data warehousing and analytics, Flyway is tailored towards database schema evolution and migration.

  2. Deployment: Amazon Redshift is a cloud-based service offered by Amazon Web Services (AWS) and requires users to provision, configure, and manage Redshift clusters in the cloud. Flyway, on the other hand, is a standalone tool that can be easily integrated into the existing database infrastructure by adding its libraries to the project. Flyway provides flexibility in terms of deployment options, including running it as a command-line tool or integrating it with build automation tools.

  3. Cost Structure: Amazon Redshift follows a pay-as-you-go pricing model where users pay for the resources they consume, including storage, compute, and data transfer. In contrast, Flyway is an open-source tool available for free, making it a cost-effective option for managing database migrations without incurring additional expenses. While Redshift offers scalability and performance benefits, users need to consider the associated costs, especially for large datasets and high query volumes.

  4. Supported Databases: Amazon Redshift is purpose-built for working with large datasets and is compatible with various data sources, including Amazon S3, RDS, and DynamoDB. Flyway, on the other hand, supports a wide range of relational databases, such as MySQL, PostgreSQL, Oracle, and SQL Server, making it a versatile choice for managing database schema migrations across different platforms.

  5. Workflow Automation: Amazon Redshift provides built-in automation features for tasks like data loading, query optimization, and performance tuning, making it easier to manage complex data warehousing workflows. In contrast, Flyway focuses on version control and migration automation, allowing developers to track changes to the database schema, apply migrations in a structured manner, and roll back changes if needed. Flyway can be integrated into Continuous Integration/Continuous Deployment (CI/CD) pipelines for automated database versioning and migration.

  6. Community Support and Documentation: Amazon Redshift benefits from the extensive documentation and support provided by AWS, offering resources like tutorials, guides, and forums for troubleshooting and best practices. Flyway, being an open-source tool, has a strong community of users and contributors who actively contribute to its development, provide feedback, and assist with issue resolution. Users can leverage community forums, GitHub repositories, and online resources to seek help and share their experiences with Flyway.

In Summary, understanding the key differences between Amazon Redshift and Flyway in terms of purpose, deployment, cost, supported databases, workflow automation, and community support can help users choose the right tool for their database management needs.

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Advice on Amazon Redshift, Flyway

datocrats-org
datocrats-org

Jul 29, 2020

Needs adviceonAmazon EC2Amazon EC2TableauTableauPowerBIPowerBI

We need to perform ETL from several databases into a data warehouse or data lake. We want to

  • keep raw and transformed data available to users to draft their own queries efficiently
  • give users the ability to give custom permissions and SSO
  • move between open-source on-premises development and cloud-based production environments

We want to use inexpensive Amazon EC2 instances only on medium-sized data set 16GB to 32GB feeding into Tableau Server or PowerBI for reporting and data analysis purposes.

319k views319k
Comments

Detailed Comparison

Amazon Redshift
Amazon Redshift
Flyway
Flyway

It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.

It lets you regain control of your database migrations with pleasure and plain sql. Solves only one problem and solves it well. It migrates your database, so you don't have to worry about it anymore.

Optimized for Data Warehousing- It uses columnar storage, data compression, and zone maps to reduce the amount of IO needed to perform queries. Redshift has a massively parallel processing (MPP) architecture, parallelizing and distributing SQL operations to take advantage of all available resources.;Scalable- With a few clicks of the AWS Management Console or a simple API call, you can easily scale the number of nodes in your data warehouse up or down as your performance or capacity needs change.;No Up-Front Costs- You pay only for the resources you provision. You can choose On-Demand pricing with no up-front costs or long-term commitments, or obtain significantly discounted rates with Reserved Instance pricing.;Fault Tolerant- Amazon Redshift has multiple features that enhance the reliability of your data warehouse cluster. All data written to a node in your cluster is automatically replicated to other nodes within the cluster and all data is continuously backed up to Amazon S3.;SQL - Amazon Redshift is a SQL data warehouse and uses industry standard ODBC and JDBC connections and Postgres drivers.;Isolation - Amazon Redshift enables you to configure firewall rules to control network access to your data warehouse cluster.;Encryption – With just a couple of parameter settings, you can set up Amazon Redshift to use SSL to secure data in transit and hardware-acccelerated AES-256 encryption for data at rest.<br>
Supported databases: Oracle, SQL Server, SQL Azure, DB2, DB2 z/OS, MySQL, MariaDB, Google Cloud SQL, PostgreSQL, Redshift, Vertica, H2, Hsql, Derby, SQLite;Supported build tools: Maven, Gradle, Ant and SBT;Works on: Windows, Mac OSX, Linux, Java and Android
Statistics
GitHub Stars
-
GitHub Stars
9.2K
GitHub Forks
-
GitHub Forks
1.6K
Stacks
1.5K
Stacks
305
Followers
1.4K
Followers
563
Votes
108
Votes
33
Pros & Cons
Pros
  • 41
    Data Warehousing
  • 27
    Scalable
  • 17
    SQL
  • 14
    Backed by Amazon
  • 5
    Encryption
Pros
  • 13
    Superb tool, easy to configure and use
  • 9
    Very easy to config, great support on plain sql scripts
  • 6
    Is fantastic and easy to install even with complex DB
  • 4
    Simple and intuitive
  • 1
    Easy tool to implement incremental migration
Cons
  • 3
    "Undo Migrations" requires pro version, very expensive
Integrations
SQLite
SQLite
MySQL
MySQL
Oracle PL/SQL
Oracle PL/SQL
Windows
Windows
Java
Java
Gradle
Gradle
Apache Maven
Apache Maven
Docker
Docker

What are some alternatives to Amazon Redshift, Flyway?

dbForge Studio for MySQL

dbForge Studio for MySQL

It is the universal MySQL and MariaDB client for database management, administration and development. With the help of this intelligent MySQL client the work with data and code has become easier and more convenient. This tool provides utilities to compare, synchronize, and backup MySQL databases with scheduling, and gives possibility to analyze and report MySQL tables data.

dbForge Studio for Oracle

dbForge Studio for Oracle

It is a powerful integrated development environment (IDE) which helps Oracle SQL developers to increase PL/SQL coding speed, provides versatile data editing tools for managing in-database and external data.

dbForge Studio for PostgreSQL

dbForge Studio for PostgreSQL

It is a GUI tool for database development and management. The IDE for PostgreSQL allows users to create, develop, and execute queries, edit and adjust the code to their requirements in a convenient and user-friendly interface.

dbForge Studio for SQL Server

dbForge Studio for SQL Server

It is a powerful IDE for SQL Server management, administration, development, data reporting and analysis. The tool will help SQL developers to manage databases, version-control database changes in popular source control systems, speed up routine tasks, as well, as to make complex database changes.

Google BigQuery

Google BigQuery

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

Liquibase

Liquibase

Liquibase is th leading open-source tool for database schema change management. Liquibase helps teams track, version, and deploy database schema and logic changes so they can automate their database code process with their app code process.

Sequel Pro

Sequel Pro

Sequel Pro is a fast, easy-to-use Mac database management application for working with MySQL databases.

DBeaver

DBeaver

It is a free multi-platform database tool for developers, SQL programmers, database administrators and analysts. Supports all popular databases: MySQL, PostgreSQL, SQLite, Oracle, DB2, SQL Server, Sybase, Teradata, MongoDB, Cassandra, Redis, etc.

Qubole

Qubole

Qubole is a cloud based service that makes big data easy for analysts and data engineers.

dbForge SQL Complete

dbForge SQL Complete

It is an IntelliSense add-in for SQL Server Management Studio, designed to provide the fastest T-SQL query typing ever possible.

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