MySQL
Change Data Capture (CDC)
Materialize supports MySQL as a real-time data source. The MySQL source uses MySQL’s binlog replication protocol to continually ingest changes resulting from CRUD operations in the upstream database. The native support for MySQL Change Data Capture (CDC) in Materialize gives you the following benefits:
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No additional infrastructure: Ingest MySQL change data into Materialize in real-time with no architectural changes or additional operational overhead. In particular, you do not need to deploy Kafka and Debezium for MySQL CDC.
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Transactional consistency: The MySQL source ensures that transactions in the upstream MySQL database are respected downstream. Materialize will never show partial results based on partially replicated transactions.
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Incrementally updated materialized views: Materialized views are not supported in MySQL, so you can use Materialize as a read-replica to build views on top of your MySQL data that are efficiently maintained and always up-to-date.
Supported versions and services
The MySQL source requires MySQL 5.7+ and is compatible with most common MySQL hosted services.
| Integration guides |
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If there is a hosted service or MySQL distribution that is not listed above but you would like to use with Materialize, please submit a feature request or reach out in the Materialize Community Slack.
Considerations
Schema changes
Materialize supports schema changes in the upstream database as follows:
Compatible schema changes
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Adding columns to tables. Materialize will not ingest new columns added upstream unless you use
DROP SOURCEto first drop the affected subsource, and then add the table back to the source usingALTER SOURCE...ADD SUBSOURCE. -
Dropping columns that were added after the source was created. These columns are never ingested, so you can drop them without issue.
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Adding or removing
NOT NULLconstraints to tables that were nullable when the source was created.
Incompatible schema changes
All other schema changes to upstream tables will set the corresponding subsource into an error state, which prevents you from reading from the subsource.
To handle incompatible schema changes, use DROP SOURCE to first drop the affected subsource,
and then ALTER SOURCE...ADD SUBSOURCE to add the
subsource back to the source. When you add the subsource, it will have the
updated schema from the corresponding upstream table.
Supported types
Materialize natively supports the following MySQL types:
bigintbinarybitblobbooleanchardatedatetimedecimaldoublefloatintjsonlongbloblongtextmediumblobmediumintmediumtextnumericrealsmallinttexttimetimestamptinyblobtinyinttinytextvarbinaryvarchar
When replicating tables that contain the unsupported data types, you can:
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Use
TEXT COLUMNSoption for the following unsupported MySQL types:enumyear
The specified columns will be treated as
textand will not offer the expected MySQL type features. -
Use the
EXCLUDE COLUMNSoption to exclude any columns that contain unsupported data types.
Truncation
Avoid truncating upstream tables that are being replicated into Materialize. If a replicated upstream table is truncated, the corresponding subsource in Materialize becomes inaccessible and will not produce any data until it is recreated.
Instead of truncating, use an unqualified DELETE to remove all rows from
the upstream table:
DELETE FROM t;
Modifying an existing source
When you add a new subsource to an existing source (ALTER SOURCE ... ADD SUBSOURCE ...), Materialize starts the snapshotting
process for the new subsource. During this snapshotting, the data ingestion for
the existing subsources for the same source is temporarily blocked. As such, if
possible, you can resize the cluster to speed up the snapshotting process and
once the process finishes, resize the cluster for steady-state.