Load MySQL data to Amazon Redshift in minutes.

Replicate your MySQL database to your data warehouse to improve the performance of your SQL queries at scale and to generate custom real-time reports and dashboards. Combine your MySQL data with other data sources such as mobile and web user analytics to make it even more valuable.

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Loading MySQL Data to Redshift: 3 Approaches
1. Binlog Replication
Suitable for Real-time MySQL replication at scale. What is Binlog MySQL's binlog keeps an ordered log of every database operation. This allows you to continuously stream and load data into Amazon Redshift. How it works 1. Create Redshift tables 2. Initial MySQL dump and load to Redshift to capture the initial state of MySQL tables 3. Continuous binlog streaming to capture updates to the table 4. Consolidation of the updated replicated table using binlog and the previous version of Redshift table Pros and cons Binlog is the most stable approach and the only one that allows near real-time replication at scale. On the downside, it doesn’t lock or affect performance of production MySQL DBs of support table alterations.
2. Full Dump & Load
Suitable for: Relatively small MySQL tables (up to 1M rows or 5M rows with increased latency). How it works 1. MySQL tables are fully dumped 2. Corresponding Amazon Redshift tables are dropped and recreated 3. Full dumps of MySQL tables are loaded to Redshift Pros and cons: Full dump and load is simple and straightforward. However, dumps are very resource intensive on the MySQL side, and you might need to lock the database to ensure consistency. Tip: It is best to use a replica instead of your master database, since it might interfere with your production application.
3. Incremental Dump and Load
Suitable for: MySQL data sets with data incrementally added, and no deletions. How it works 1. MySQL tables are periodically queried for new updates 2. Updates are loaded into Amazon Redshift 3. A consolidation query reconstructs the original table: SELECT * FROM my_table WHERE last_update > #{last_import} Pros and cons: In each iteration, only the updates are extracted and loaded which reduces load. However, this method cannot capture row deletions or row alterations (unless actively queried in each iteration).

MySQL to Redshift - Should you do it yourself or use a third party solution?
When starting out with small data volumes and working in a simple Full Dump & Load approach, it is possible to build your own MySQL to Redshift solution. However, if you have the following requirements, things get more complex: - Tables bigger than 1GB - Over a million daily updates to MySQL tables - Frequent schema changes - High throughput, high availability, low latency If you are in this situation, consider using a data pipeline service to help you integration your MySQL to Amazon Redshift. Alooma offers a production grade MySQL to Redshift pipeline to get you up and running in minutes. Learn more about MySQL to Redshift replication here.

Export your MySQL data along with all of
your other data sources to Amazon Redshift.


MySQL is the most popular open source database used by millions of mobile and web applications.

Amazon Redshift
Amazon Redshift

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools.

Visualize, debug, and filter your MySQL data in real-time.
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