Hello and welcome to a brand new year! With the new year, we thought we’d take this opportunity to show you how SQLMorph has changed over the last year.
SQLMorph, our free-to-use transpiler built to convert SQL statements from source to target, has seen a lot of changes as customers and internal engineers have continued to use the platform. We continue to proactively monitor exceptions thrown by the code base and iterate on providing fixes without users needing to report them, but as always we welcome your feedback!
A Year In Review
SQLMorph was designed and implemented to allow for quicker execution of customer projects, migrations, and individual tasks. As you can imagine, converting hundreds of thousands of lines of SQL manually when an enterprise migrates from one database to another is a time-consuming task.
SQLMorph and the SQLMorph API allow you to quickly script all of the SQL transpilation.
While we’d love to show transpilation metrics for all of 2021, currently we only store the last three months of statistics on usage for SQLMorph. This is something we aim to improve in 2022, so look forward to more complete metrics in 2023. However, for the last three months, we’ve had:
- 11,698 successful queries
- Note this doesn’t include bulk translations
- 93% successful transpilation rate
Over the course of the entire year, we were able to pull some metrics:
- 527 Jira Tickets closed/resolved
- 437 commits on the master branch
- This is lower than the number of Jira tickets as some pull requests to develop are squashed and/or may cover multiple Jira tickets
- 500% increase in distinct users
Real World Usage
While we frequently talk about the advantages of using a tool like SQLMorph, one of the important questions is “How well does this tool do in the real world?” This is exactly what we have started to capture as clients use SQLMorph on their various projects.
In the following example, a customer is migrating their data warehousing from Hadoop/Hive to Snowflake. This migration involves a lot of tasks to migrate the data, but the customer had almost 100,000 lines of SQL that needed to be translated. SQLMorph was able to accomplish this with a 100% conversion rate.
Since SQLMorph provides some informational and warning messages on translations that are not exact, it allowed developers to focus on those specific queries to validate parity between the two systems instead of every single line of code.
With only 2 distinct warnings across 7394 statements, developers only needed to focus on 0.02% of all SQL statements!