Important Characteristics of Oracle Autonomous Data Warehouse Cloud

Oracle Autonomous Data Warehouse Cloud Service is based on applied machine-learning to automatically tune and optimize performance. Built on the next generation Oracle Autonomous Database technology using artificial intelligence to deliver unprecedented reliability, performance and highly elastic data management to enable data warehouse deployment in seconds. Here are some important characteristics of Oracle Autonomous Data Warehouse Cloud.

init.ora parameters

Autonomous Data Warehouse Cloud automatically configures the database initialization parameters based on the compute and storage capacity you provision. You do not need to set any initialization parameters to start using your service. But, you can modify some parameters if you need to.

  • Parameters optimized for DW workloads
  • Memory, parallelism, sessions configured based on number of CPUs
  • Users can modify a limited set of parameters, e.g. NLS settings

Tablespace management

The default data and temporary tablespaces for the database are configured automatically. Adding, removing, or modifying tablespaces is not allowed.

  • Pre-defined data and temporary tablespaces
  • Users cannot create/modify tablespaces


Compression is enabled by default. Autonomous Data Warehouse Cloud uses Hybrid Columnar Compression for all tables by default, changing the compression method is not allowed.

  • All tables compressed using Hybrid Columnar Compression
  • Users cannot change compression method or disable compression

Optimizer stats gathering

Autonomous Data Warehouse Cloud gathers optimizer statistics automatically for tables loaded with direct-path load operations. For example, for loads using the DBMS_CLOUD package the database gathers optimizer statistics automatically.

  • Stats gathered automatically during direct load operations
  • Users can gather stats manually if they want

Optimizer hints

Autonomous Data Warehouse Cloud ignores optimizer hints and PARALLEL hints in SQL statements by default. If your application relies on hints you can enable optimizer hints by setting the parameter OPTIMIZER_IGNORE_HINTS to FALSE at the session or system level using ALTER SESSION or ALTER SYSTEM. You can also enable PARALLEL hints in your SQL statements by setting OPTIMIZER_IGNORE_PARALLEL_HINTS to FALSE at the session or system level using ALTER SESSION or ALTER SYSTEM.

– Hints ignored by default

– Users can enable hints explicitly

Result cache configuration

Oracle Database Result Cache is enabled by default for all SQL statements. Changing the result cache mode is not allowed.  

  • Result Cache is enabled by default
  • Changing the result cache mode is not allowed.

Parallelism enabled by default

Parallelism is enabled by default. Degree of parallelism for SQL statements is set based on the number of OCPUs in the system and the database service the user is connecting to.

  • Degree of parallelism for SQL statements = OCPU
  • Parallel DML is enabled by default
  • you can disable parallel DML in your session


The Overview and Activity tabs in the Service Console provide information about the performance of the service. The Activity tab also shows past and current monitored SQL statements and detailed information about each statement.

  • Simplified monitoring using the web-based service console
  • Historical and real-time performance charts
  • Real-Time SQL Monitoring to monitor running and past SQL statements
  • Historical data load monitoring

Data Loading

You need to use Oracle Data Pump Export to export your existing Oracle Database schemas to migrate them to Autonomous Data Warehouse Cloud using Oracle Data Pump Import.

  • Partitioned tables are converted into non-partitioned tables.
  • Storage attributes for tables are ignored.
  • Index-organized tables are converted into regular tables.
  • Constraints are converted into rely disable novalidate constraints.
  • Indexes, clusters, indextypes, materialized views, materialized view logs, and zone maps are excluded during Data Pump Import.

Scaling Resources

You can scale your Autonomous Data Warehouse Cloud on demand by adding CPU cores or storage capacity (TB). From CLOUD My Services, access the Autonomous Data Warehouse Cloud you want to scale.

  • Type of change, increase or decrease select Scale Up
  • Enter a value for CPU Core Count Change. The default is 0, for no change
  • Enter a value for Storage Capacity (TB) Change. The default is 0, for no change

Backing Up and Restoring

Autonomous Data Warehouse Cloud automatically backs up your database for you. The retention period for backups is 60 days. You can restore and recover your database to any point-in-time in this retention period.

  • Provide weekly full backups and daily incremental backups.
  • Autonomous Data Warehouse Cloud backs up your database automatically.
  • You can do manual backups using the cloud console.
  • You can initiate recovery for your ADWC
  • ADWC automatically restores and recovers your database to the point-in-time