Copy (ELT) Google Cloud SQL for MySQL data to Elasticsearch in a few clicks and keep it up to date automatically.
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If needed, configure replication settings — exclude certain fields, change table naming, apply data hashing, add filters for data.
Configure scheduling and run replication every month, week or day, at specific time or recurrently at any interval, up to once per minute.
View all the integration runs for any period, get email notifications and detailed per-record error logs in case of errors to help you be aware of the situation.
Skyvia's Replication is an easy-to-use ELT tool that lets you set up Google Cloud SQL for MySQL replication to Elasticsearch in several minutes. It allows you to copy Google Cloud SQL for MySQL objects (including data) to Elasticsearch and keep the copy up to date.
You don’t need to prepare the Elasticsearch database — Skyvia creates the indexes, corresponding to the Google Cloud SQL for MySQL objects, automatically. Besides, it can automatically modify target Elasticsearch indexes according to new fields added in Google Cloud SQL for MySQL.
With Skyvia you can extract and load all the data from a Google Cloud SQL for MySQL object or disable loading for some Google Cloud SQL for MySQL object fields. You can also configure filters for data to replicate.
Skyvia allows you to hash sensitive data, like names and emails. You can conceal personally identifiable information for better compliance and preserve analytical value of replicated data at the same time.
Skyvia not just copies Google Cloud SQL for MySQL data to Elasticsearch once, it can keep your Elasticsearch indexes up-to-date with Google Cloud SQL for MySQL automatically, ensuring you always have fresh data for data analysis without any user intervention.
History mode allows you to store all versions of Google Cloud SQL for MySQL records in your Elasticsearch indexes instead of keeping only the current versions. You can select the mode for each object separately.
By default, target indexes are named in the same way as source objects. Skyvia offers settings that allow you to change target index names — for all Google Cloud SQL for MySQL objects in the integration or for each one separately. This is especially useful if you load several Google Cloud SQL for MySQL instances into Elasticsearch, and want to use separate indexes for them.
Skyvia combines a high-performance optimized batch data loading into Elasticsearch with a granular, per-record data insertion and error logging in case of any errors.
If you need more than just to copy data from Google Cloud SQL for MySQL to Elasticsearch, you may use Skyvia's powerful ETL functionality for Google Cloud SQL for MySQL and Elasticsearch integration . Skyvia's Import tool will correctly extract Google Cloud SQL for MySQL data, transform it, and load to Elasticsearch when Elasticsearch indexes have different structure than Google Cloud SQL for MySQL objects. Moreover, Skyvia Import allows loading data in any direction, supporting Reverse ETL scenario.
For more complex cases, you can use Data Flow and Control Flow tools. They are designer-based solutions for creating complex data pipelines, involving not only Google Cloud SQL for MySQL and Elasticsearch connectors, but any number of connectors in one integration. With these tools you can automate data workflows, involving custom logic, complex multistage transformations, combine data from different sources, load them into multiple destinations at once and many more.
Use flexible scheduling settings to automate replication
You can find detailed logs for each execution in the package Run History.
Enable email notifications and always know if anything goes wrong.
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Integrate Google Cloud SQL for MySQL and Elasticsearch data with minimal effort with Skyvia.
