Oracle Overview

Oracle is an object-relational database management system created by the Oracle Corporation. Fivetran’s integration platform replicates data from your Oracle source database and loads it into your destination.

Supported serviceslink

Fivetran supports three different Oracle database services:

• Generic Oracle
• Oracle RAC PRIVATE PREVIEW
• Amazon RDS Oracle

Supported configurationslink

Fivetran supports the following Oracle configurations:

* Maximum throughput is your connector’s end-to-end update speed, measured in megabytes per second (MBps). We calculate your maximum throughput by averaging the number of rows synced per second during your connector’s last 3-4 syncs. To learn more about sync speed, see the Replication speeds section.

Which Oracle database types we support depends on your database service.

Known limitationslink

• There are some rare Oracle configurations that cause our initial sync queries to stall on some tables. To ensure that you are not affected, complete an initial sync of your data before you buy Fivetran.
• If you have uncommitted transactions, our incremental update process will halt until the transactions are committed. If the transactions remain uncommitted for more than six hours, you may be forced to re-sync.

Featureslink

Setup guidelink

Follow our step-by-step setup guides for specific instructions on how to set up your Oracle database type:

• Generic Oracle
• Oracle RAC PRIVATE PREVIEW
• Amazon RDS Oracle

If you have Amazon RDS Oracle and want to connect via SSH tunnel, see the RDS Tunnel setup guide.

Sync overviewlink

Once Fivetran is connected to your Oracle source database, we pull a full dump of all selected data from your database. We then pull all your new and changed data at regular intervals using your archived redo logs and LogMiner. If data in the source changes (for example, you add new tables or change a data type), Fivetran automatically detects and persists these changes to your destination.

Replication speedslink

Two major factors can cause disparities between our estimates and the exact replication speed for your Fivetran-connected databases: network latency and discrepancies in the format of the data we receive versus how the data is stored at rest in the data destination.

The ability to sync changes quickly also depends on the sync frequency you configure. The risk of the sync falling behind, or being unable to keep up with data changes, decreases as the sync frequency increases. We recommend a higher sync frequency for data sources with a high rate of data changes.

To measure the rate of new data in your database, check the disk space usage metrics over time for databases hosted on cloud providers. For self-hosted databases, you can run the following query to determine disk space usage:

SELECT SUM(bytes)/1024/1024 AS MB FROM dba_segments;

Schema informationlink

Fivetran tries to replicate the exact schema and tables from your Oracle source database to your destination according to our standard database update strategies. We create schemas in your destination that map directly to the schemas in your source Oracle database, ensuring that the data in your destination is in a familiar format to work with.

When you connect to Fivetran and specify a source database, you also select a schema prefix. We map the schemas we discover in your source database to your destination and prepend the destination schema name with the prefix you selected.

Fivetran-generated columnslink

Fivetran adds the following columns to every table in your destination:

• _fivetran_deleted (boolean) marks rows that were deleted in the source database.
• _fivetran_synced (UTC timestamp) keeps track of when each row was last successfully synced.
• _fivetran_id (string) is a unique ID that Fivetran uses to avoid duplicate rows in tables that do not have a primary key.

We add these columns to give you insight into the state of your data and the progress of your data syncs.

Type transformations and mappinglink

As we extract your data, we match Oracle data types to types that Fivetran supports. If we don’t support a certain data type, we automatically change that type to the closest supported type or, in some cases, don’t load that data at all. Our system automatically skips columns of data types that we don’t accept or transform.

The following table illustrates how we transform your Oracle data types into Fivetran supported types:

† The UNKNOWN type is used in Fivetran’s core pipeline when type inference is necessary. This is the case for the Oracle’s NUMBER type, because it can hold short integers, integers, long integers, floating-point and double-precision floating-point numbers, and big decimal numbers. There is no one single clear mapping available for these types, so Fivetran maps them automatically based on observed values.

* The NUMBER and FLOAT types with high precision and scale may be rounded by LogMiner in Oracle 11g. This does not happen in Oracle 12c or higher.

If we are missing an important type that you need, please reach out to support.

In some cases, when loading data into your destination, we may need to convert Fivetran data types into data types that are supported by the destination. For more information, see the individual data destination pages.

Excluding source datalink

If you don’t want to sync all the data from your source database, you can exclude schemas, tables, or columns from your syncs on your Fivetran dashboard. To do so, go to your connector details page and un-check the objects you would like to omit from syncing. For more information, see our Column Blocking documentation.

You can also use SELECT permissions if you want to exclude specific schemas and tables from syncing. The Fivetran user can only discover schemas and tables for which it has been given explicit SELECT permission. Note that permissions will not shield confidential data, such as PII (Personally Identifiable Information), from Fivetran because they do not apply to archived redo logs. Via the archived redo log files, Fivetran has access to the full contents of any changed rows of all tables that pass through your system. However, we filter out the prohibited data at the earliest possible stage of our syncs and do not load it into your destination.

Initial synclink

When Fivetran connects to a new database, we first copy all rows from every table in every schema for which we have SELECT permission (except for those you excluded in your Fivetran dashboard) and add Fivetran-generated columns. We copy rows by performing a SELECT statement on each table. We import each table in full before moving onto the next one.

The duration of initial syncs can vary depending on the number and size of tables to be imported. We therefore interleave incremental updates with the table imports during the initial sync. If the import of a table takes an hour or longer, we process any accumulated incremental updates before we begin importing the next table.

Updating datalink

Once the initial sync is complete, Fivetran performs incremental updates of any new or modified data from your source database. We detect modified rows in the source tables using LogMiner. We use the system change number (SCN) to keep track of our place in the logs at the end of each update to ensure a seamless hand-off between syncs. During each update, we sync all committed transactions to the destination.

We use LogMiner to process your archived redo log files. LogMiner only captures the changes from archived log files, not from active log files. By default, filling the current redo log file automatically triggers a log switch, which changes the file to an archived log file. The default redo log file size is 4MB, but the size can be larger depending on the configuration. If you have a quiet database with little activity, it can take a long time for you to fill a log file and trigger a log switch. In this case, you must run the command ALTER SYSTEM SWITCH LOGFILE; in your database to trigger the log switch. Alternatively, you can configure the time-based automatic log switch by running the command ALTER SYSTEM SET ARCHIVE_LAG_TARGET=900 scope=BOTH;. This configuration guarantees that the log file switch will occur less than 15 minutes after the last log switch.

When we encounter an uncommitted transaction, we terminate the active sync and re-try at the next sync interval (for example, if you have your sync interval set to 30 minutes, we will re-try the sync in 30 minutes). Re-trying the sync ensures that we eventually sync the data from the uncommitted transaction. We also generate a warning in your Fivetran dashboard with details about that uncommitted transaction. If the transaction remains uncommitted for more than 24 hours, you may be forced to re-sync.

When we encounter any DDL events (excluding GRANT) tied to a table, we must re-import the table due to limitations of the LogMiner.

Tables with a primary keylink

We merge changes to tables with primary keys into the corresponding tables in your destination:

• An INSERT in the source table generates a new row in the destination with _fivetran_deleted = FALSE.
• A DELETE in the source table updates the corresponding row in the destination with _fivetran_deleted = TRUE.
• An UPDATE in the source table updates the data in the corresponding row in the destination.

If we detect that your primary key has changed, we handle DELETEs and UPDATEs differently:

• If you have set SUPPLEMENTAL LOG DATA (ALL) on your source table, we update the row with the old primary key value with _fivetran_deleted = TRUE. We then insert a row with the new primary key value with _fivetran_deleted = FALSE.
• If you have not set SUPPLEMENTAL LOG DATA (ALL) on your source table, we do not update the row with the old primary key value because we can’t identify it. We insert a row with the new primary key value with _fivetran_deleted = FALSE.

Note: If we detect that your primary key has changed and you have not set SUPPLEMENTAL LOG DATA (ALL) on your source table, we send you a warning telling you to set SUPPLEMENTAL LOG DATA (ALL) on the table.

Tables without a primary keylink

For tables without a primary key, we designate our _fivetran_id column as the primary key. We populate this column in one of two ways:

• If the table is partitioned and row movement is enabled, we use a hash of the column’s non-Fivetran values to populate our _fivetran_id column.
• Otherwise, we use Oracle’s ROWID pseudo column to populate our _fivetran_id column.
  • If you enable row movement later, we automatically re-sync the table and use a hash of the column’s non-Fivetran values to populate our _fivetran_id column.
  • If we detect any DDL operations (excluding GRANT), we automatically re-sync the table and re-import its contents with the newly assigned ROWIDs.

Deleted datalink

We do not delete rows from your destination. When a row is deleted from the source table, we set the _fivetran_deleted column value of the corresponding row in the destination to TRUE.

Excluded tableslink

Fivetran does not sync the following tables:

• Temporary tables
• System-generated supplemental tables (for example, IOT or MLOG$ tables)
• System tables (for example, those in the SYSTEM tablespace or those owned by SYS user)

Migrating Service Providerslink

If you want to migrate service providers, we will need to do a full re-sync of your data because the new service provider won’t retain the same change tracking data as your original Oracle database.