Considerations and Support Information

Ensure that you understand what is supported, and any current limitations, dependencies, and required tasks before you create data assets in Data Integration.

OCI Vault Secrets and Oracle Wallets

Oracle Cloud Infrastructure Data Integration is integrated with Oracle Cloud Infrastructure Vault to enable you to manage sensitive information using vaults, keys, and secrets.

A vault is a container for keys and secrets. Secrets store credentials such as required passwords for connecting to data sources. You use an encryption key in a vault to encrypt and import secret contents to the vault. Secret contents are based64-encoded. Oracle Cloud Infrastructure Data Integration uses the same key to retrieve and decrypt secrets when creating a data asset and connecting to the data source.

For most data source types, you can use a secret in OCI Vault to store the password for the default connection in a data asset. To create a vault and a secret, see Creating a Vault and Creating a Secret in a Vault.

When you create a data asset, you provide the OCID of the secret in the connection details, so you don't have to enter the actual password. To copy the secret OCID, see Getting a Secret's Details.

For Oracle Database, Oracle Autonomous Data Warehouse, and Oracle Autonomous Transaction Processing sources, you have the option to use secrets for the Oracle wallet and passwords instead of uploading the wallet and entering the wallet password when you create your data asset.

To use an Oracle wallet with secrets in OCI Vault, you must:

  1. Provide a wallet password when you download the wallet.
  2. Remove the .p12 file from the dowloaded wallet zip.
  3. Use any base64 encoder to encode the modified wallet zip to base64.
  4. Copy the base64-encoded data to a secret in a vault.
  5. Create a secret for the wallet password.
  6. Create a secret for the database password.

To use secrets in OCI Vault, ensure that you have the following policy:

allow any-user to read secret-bundles in compartment <compartment-name> where ALL {request.principal.type = 'disworkspace', request.principal.id = '<workspace-ocid>'}

Use the following policy to enable a group of users who aren't administrators to use secrets with Oracle Autonomous Data Warehouse and Oracle Autonomous Transaction Processing:

allow group <group-name> to read secret-bundles in compartment <compartment-name>

Supported Data Sources for Data Assets

The following table lists the data sources that you can use with Data Integration.

Data Source Type Version Source Target
Amazon RDS for SQL Server 2019 Yes No
2017 Yes No
2016 Service Pack 2 Yes No
2014 Service Pack 3 Yes No
2012 Service Pack 4 Yes No
Amazon Redshift Amazon Redshift Yes No
Apache Hive CDH 5.4 and higher Yes No
Apache 1.0, 2.0, 3.0, and higher Yes Yes
Hadoop Distributed File System (HDFS) 3.1.2 Yes Yes
Azure SQL Database 11.0 and higher Yes No
12.0 and higher Yes No
Microsoft Azure Synapse Analytics 12.0 and higher Yes No
Microsoft SQL Server 2022 Yes No
2019 Yes No
2017 Yes No
2016 Service Pack 2 Yes No
2014 Service Pack 3 Yes No
2012 Service Pack 4 Yes No
MySQL 5.7.x and 8.0.x Yes Yes
MySQL HeatWave 8.0 and higher Yes No
MySQL on Amazon RDS 5.7.x and 8.0.x Yes No
Amazon S3 Amazon S3 Yes No
Autonomous Data Warehouse 18c/19c Yes Yes
Autonomous Transaction Processing 18c/19c Yes Yes
Oracle Database 11g Yes (except SQL task stored procedure) Yes
12.1 Yes Yes
12.2 Yes Yes
18 Yes Yes
19 Yes Yes
21 Yes Yes

Oracle Database on Oracle Cloud Infrastructure

11g Yes (except SQL task stored procedure) Yes
12.1 Yes Yes
12.2 Yes Yes
18 Yes Yes
19 Yes Yes
Oracle Peoplesoft

CRM 8.4 and higher

PeopleTools 8.49 and higher

Yes No
Oracle Siebel 8.0 and higher Yes No
Oracle E-Business Suite 12.0.4 and higher Yes No
Exadata DB Systems 11g Yes (except SQL task stored procedure) Yes
12.1 Yes Yes
12.2 Yes Yes
18 Yes Yes
19 Yes Yes
Oracle Cloud Infrastructure Object Storage Latest Yes Yes
Oracle on Amazon RDS 12.1 Yes No
12.2 Yes No
18 Yes No
19 Yes No
21 Yes No
Oracle Fusion Applications using Oracle Business Intelligence Cloud Connector (BICC)

BICC API version 13.20.10 and higher

Fusion Applications version 13.20.10 (20 Oct) and higher

YesNo
Oracle Fusion Applications using Oracle Business Intelligence Publisher (BIP) 11.1.1.9 and higher Yes No
PostgreSQL 12.0 and higher Yes No
11.0 and higher Yes No
10.1 Yes No
9.6, 9.5, 9.4, 9.3, 9.2, 9.1, and 9.0 Yes No
8.4, 8.3, and 8.2 Yes No
IBM DB2 DB2 V11.1 and higher for Linux, UNIX, and Windows Yes No
DB2 V10.1 and higher for Linux, UNIX, and Windows Yes No
DB2 V9.1 and higher for Linux, UNIX, and Windows Yes No
DB2 V8.x and higher for Linux, UNIX, and Windows Yes No
DB2 V12 and higher for z/OS Yes No
DB2 V11 and higher for z/OS Yes No
DB2 V10 and higher for z/OS Yes No
DB2 V9.1 and higher for z/OS Yes No
DB2 UDB V8.1 for z/OS Yes No
DB2 i 7.1 and higher Yes No
DB2 i 6.1 and higher Yes No
DB2 V5R4 and higher for i 5/OS Yes No
Amazon Web Services (AWS) Aurora PostgreSQL 1.0 and higher Yes No
Influx DB 1.8 and 2.x Yes No
REST OpenAPI 3.0.0 and higher Yes No
Snowflake NOT APPLICABLE Yes No
Salesforce Salesforce API 56.0 Yes No

Supported Object Types

For Oracle Cloud Infrastructure Object Storage and Amazon S3 data assets, Data Integration supports the following object types:

  • CSV
  • JSON
  • Parquet
  • Avro
  • Excel (Currently, only XLSX files are supported.)

Note that only read and write of primitive data types are supported.

Supported Compression Types

For Oracle Cloud Infrastructure Object Storage data assets, Data Integration supports the following compression types or methods for using the CSV or JSON object file type with a source or target operator:

  • Auto (Default)
  • Gzip
  • Bzip2
  • Deflate
  • Lz4
  • Snappy

For Parquet and Avro file types, only Auto (Default) is supported.

If a source file is compressed, the compression type is the compression algorithm that's used. If you don't know the compression algorithm, then use the Auto (Default) compression type.

Data Types Not Supported

Data source Data types not supported
Oracle Database
  • RAW
  • ROWID
  • UROWID
  • BFILE
  • TIMESTAMP WITH LOCAL TIMEZONE
  • INTERVAL DAY TO SECOND
  • INTERVAL YEAR TO MONTH
  • XMLTYPE
  • SDO_GEOMETRY
  • NCHAR
  • NVARCHAR

Hierarchical Data Types

Data Integration supports hierarchical data types in source and target data entities.

To read and write data with hierarchical data types, currently you can use only generic REST data assets and file storage data assets such as OCI Object Storage, Amazon S3, and HDFS. The JSON file format is supported by generic REST data assets. For file storage data assets, the following file formats are supported:

  • JSON and multi-line JSON
  • Avro
  • Parquet

The supported hierarchical data types are the Array, Struct, and Map complex types. You can perform any type of file to file transformation, such as JSON to Avro or Avro to JSON.

Before using hierarchical data entities and complex types, ensure that you understand the supported capabilities in Data Integration when working with components and performing tasks.

Task/ComponentSupportLimitation
Prepare data sources
  • Generic REST data asset and JSON file format
  • OCI Object Storage data asset and JSON, multi-line JSON, Avro, and Parquet file formats
  • Array, Struct, and Map complex types
  • Array is not supported in Avro and Parquet file formats
Add and configure a source operator
  • JSON, Avro, and Parquet file types
  • Exclude and Rename rules on first-level fields of ARRAY_TYPE, COMPOSITE_TYPE (Struct), and MAP_TYPE
  • Simplified data structure view of a complex type is displayed
  • Attributes tab: Cannot apply rules on nested fields
  • Data tab: Data Profile does not display for complex types
Add and configure a target operator

Select the Create new data entity checkbox:

  • JSON, Avro, and Parquet hierarchical file formats
  • Array, Struct, and Map complex types

Select existing data entity:

  • File: JSON, Avro, and Parquet hierarchical file formats
  • Database: Only Oracle Database and Oracle Database on Oracle Cloud Infrastructure
Use shape operators
  • Array and Struct complex types are supported in all operators
  • For Union operator, only Union All (include duplicate rows) is supported with Array and Struct complex types
  • For Union All, Minus, Intersect, Filter, and Split operators: Map complex type is not supported
  • Union (eliminate duplicate rows) is not supported
  • Attribute bulk selections and patterns are not supported for complex types. For example, %MACRO_INPUT% for bulk selection of attributes is not supported in the Expression Builder.
Map attributes
  • First-level fields of JSON, Avro, and Parquet hierarchical data entities can be mapped
  • To map a nested field, create an expression for the nested field, and then map the derived field
  • Nested fields of hierarchical data entities cannot be mapped directly

For example, NAME and EMAIL can be mapped. F_NAME and L_NAME in NAME cannot be mapped directly. EMAILID and EMAILTYPE in EMAIL cannot be mapped directly:

{
   "CUST_ID":1333,
   "NAME":{
      "F_NAME":"Sam",
      "L_NAME":"Smith"
   },
   "EMAIL":[
      {
         "EMAILID":"abc@oracle.com",
         "EMAILtype":"work"
      },
      {
         "EMAILID":"abc@othermail.com",
         "EMAILtype":"personal"
      }
   ],
   "GENDER":"Male"
}
Use data transformations (Data tab)
  • Exclude and Rename transformations on first-level fields of ARRAY_TYPE, COMPOSITE_TYPE, and MAP_TYPE
  • All other transformations and bulk transformations are not supported for complex types

Unicode Support

Data Integration supports the Unicode standard, which is a universal character encoding standard for written characters and text in any language. The Unicode standard provides a unique number for every character regardless of the platform, device, or application. For example, 0041 is the Unicode character for the English letter "A".

Data Integration supports Unicode characters (including multibyte characters) in data and metadata.

Unicode support in data means that the attributes and attribute values in your source and target data assets can include Unicode and multibyte characters. You can also enter Unicode and multibyte characters in expressions. For JSON and CSV Object Storage data assets, the default encoding is UTF-8, and you cannot change it.

Unicode support in metadata means that the data entity and schema names of your data assets can include Unicode and multibyte characters. You can also enter Unicode and multibyte characters for names and descriptions when working with objects in Data Integration.

In the Unicode standard, a unique number assigned to a Unicode character is a code point. Currently, Data Integration supports the following Unicode code points and range of code points:

Code Point or RangeCharacterNumber of Characters Supported
Basic Latin characters
0024$ (dollar sign)1
0041 - 005AA to Z26
005F_ (underscore)1
0061 - 007Aa to z26
Latin-1 Supplement characters
00C0 - 00D6Latin-1 Supplement characters with accents23
00D8 - 00F631
00F8 - 00FF8
Characters in 46 ranges from Latin Extended-A to Greek Extended
0100 - 1FFFCharacters in the following named ranges: Latin Extended-A, Latin Extended-B, IPA Extensions, Spacing Modifier Letters, Combining Diacritical Marks, Greek and Coptic, Cyrillic, Cyrillic Supplementary, Armenian, Hebrew, Arabic, Syriac, Thaana, Devanagari, Bengali, Gurmukhi, Gujarati, Oriya, Tamil, Telugu, Kannada, Malayalam, Sinhala, Thai, Lao, Tibetan, Myanmar, Georgian, Hangul Jamo, Ethiopic, Cherokee, Unified Canadian Aboriginal Syllabics, Ogham, Runic, Tagalog, Hanunoo, Buhid, Tagbanwa, Khmer, Mongolian, Limbu, Tai Le, Khmer Symbols, Phonetic Extensions, Latin Extended Additional, Greek Extended7936
Characters in 4 ranges from Hiragana to Hangul Compatibility Jamo
3040 - 318FCharacters in the following named ranges: Hiragana, Katakana, Bopomofo, Hangul Compatibility Jamo336
Characters in 4 CJK (Chinese, Japanese, and Korean) ranges
3300 - 337FCJK Compatibility characters128
3400 - 3D2DCJK Unified Ideographs Extension A characters2350
4E00 - 9FFFCJK Unified Ideographs characters20992
F900 - FAFFCJK Compatibility Ideographs characters512

Understanding Data Type Mappings

Data types from the source and target systems you use are mapped to and mapped from a core set of generic data types in Oracle Cloud Infrastructure Data Integration.

In the set of generic data types, some types have length, scale, and other properties that you can use to further constrain the data type.

The Expression operator in Data Integration does not yet support all the generic data types. You can create a new attribute based on a generic data type only if the generic type is supported.

Network Configurations

Your network configurations depend on the source and target data assets you're using with the Data Integration service, and where the assets are located.

See the Understanding VCN Configuration for Data Integration blog to identify the options for your needs.

A workspace can have an attached Virtual Cloud Network (VCN). For data sources in a private network, create a VCN with at least one regional subnet. Only regional subnets are supported, and DNS hostnames must be used in the subnets. Depending on the location of your data sources, you might have to create other network objects such as service gateways, network security groups, and Network Address Translation (NAT) gateways.

In general, for data sources that are accessible from the internet:

  • If a workspace has an attached VCN: Data Integration can connect directly through a Network Address Translation (NAT) gateway on the VCN of the workspace.
  • If a workspace does not have an attached VCN: Data Integration can connect directly using public IP addresses.

Resources, such as workspaces, with private IPs defined in any subnet can access other private resources in different virtual cloud networks and regions through Service gateways or NAT gateways using local or remote peering gateways.

You can also combine gateways when you need to access both Object Storage and Autonomous Data Warehouse. For example, for public connectivity, you would need both a Service gateway for Object Storage and a NAT gateway for Autonomous Data Warehouse.

For data sources that are not accessible from the internet, other options include:

  • Create a workspace with a private endpoint enabled, with the private endpoint in the same subnet as the data source.

  • Use Oracle Cloud Infrastructure FastConnect.

  • Use Oracle Cloud Infrastructure VPN Connect (also referred to as an IPSec VPN).

Note, however, that Oracle Cloud Infrastructure FastConnect and Oracle Cloud Infrastructure VPN Connect must be used when these sources are in private domains:

  • Oracle on Amazon RDS
  • MySQL on Amazon RDS
  • Amazon RDS for SQL Server
  • Microsoft Azure SQL Database

Oracle Cloud Infrastructure Networking documentation: