As data volumes continue to grow, performance becomes a critical factor in database operations. Whether you’re working with data warehouses, analytics workloads, or large batch jobs, speed and efficiency matter more than ever.
Oracle has long supported Parallel DML (Data Manipulation Language) to accelerate operations. But with the release of Oracle Database 23c, a major enhancement has arrived—Unrestricted Parallel DML.
This new capability removes long-standing limitations and makes parallel processing more flexible, efficient, and powerful.
Let’s explore what’s changed, why it matters, and how you can benefit from it.
What is Parallel DML?
Parallel DML allows Oracle to execute operations like:
INSERTUPDATEDELETEMERGE
by breaking them into smaller tasks that run simultaneously.
Instead of processing a large dataset sequentially, Oracle:
- Splits the workload
- Distributes it across multiple processes
- Executes operations in parallel
👉 The result? Significantly faster data processing
Where Parallel DML is Most Useful
Parallel DML is especially beneficial in:
🏢 Data Warehousing
- Managing historical data
- Updating summary tables
- Bulk data loading
📈 Analytics Workloads
- Processing large datasets
- Running transformations
🔄 Batch Jobs (OLTP Systems)
- Long-running operations
- Periodic updates
👉 Any workload involving large data volumes can benefit.
Limitations Before Oracle 23c
Before Oracle 23c, Parallel DML had several strict limitations.
❌ “One Touch” Restriction
Once a table was modified using Parallel DML:
- You could not query or modify it again in the same transaction
❌ No Follow-Up Operations
After a parallel DML operation:
- No additional DML or queries on that table were allowed
❌ Transaction Rejection
If you attempted to access the same table again:
- The transaction would fail
❌ Frequent Commits Required
To continue working:
- You had to commit after each operation
👉 These limitations made Parallel DML:
- Hard to use
- Less flexible
- Inefficient for complex workflows
What’s New in Oracle 23c?
Oracle 23c introduces Unrestricted Parallel DML, removing many of these limitations.
✅ Key Improvements:
🔹 Multiple Operations in Same Transaction
You can now:
- Run multiple DML statements on the same table
- Within the same session and transaction
🔹 Query After Parallel DML
You can:
- Query the table after modifying it
- Without needing a commit
🔹 No More “One Touch” Limitation
Tables can now:
- Be accessed multiple times
- Just like normal (serial) operations
🔹 Multiple Direct Loads
You can:
- Perform multiple direct loads
- Without committing between each step
👉 This makes Parallel DML behave much closer to standard SQL operations.
Why This Matters
🔹 1. Improved Performance
Parallel execution already improves speed, but now:
- Fewer commits = less overhead
- Continuous processing = faster workflows
👉 Better performance for large-scale operations
🔹 2. Simplified Development
No more complex logic to:
- Break transactions
- Manage commits
👉 Developers can write cleaner, simpler SQL
🔹 3. Better Scalability
Large datasets can now be:
- Processed more efficiently
- Without artificial restrictions
👉 Ideal for modern data platforms
🔹 4. Real-Time Processing
Since commits are no longer required between steps:
- Workflows become more continuous
- Processing becomes more dynamic
Remaining Restrictions
While many limitations are removed, some still apply.
❌ Supported Table Types Only
Parallel DML works with:
- Heap tables
Not supported:
- Clustered tables
- Index Organized Tables (IOTs)
❌ ASSM Requirement
Tables must use:
- Automatic Segment Space Management (ASSM)
Not supported:
- Non-ASSM tables
- Temporary tables without ASSM
- Tablespaces with uniform extents
👉 These are important to consider when designing your schema.
How to Enable Parallel DML
Parallel DML is disabled by default.
✅ Enable at Session Level:
ALTER SESSION ENABLE PARALLEL DML;
✅ Enable Using Hint:
INSERT /*+ ENABLE_PARALLEL_DML */ INTO table_name ...
❌ Disable for Specific Statements:
INSERT /*+ DISABLE_PARALLEL_DML */ INTO table_name ...
Important Behavior Notes
- Parallel DML and Serial DML use different:
- Locking mechanisms
- Disk space handling
- When enabled:
- All DML statements are considered for parallel execution
- When disabled:
- No DML runs in parallel (even with hints)
Real-World Use Cases
🔹 Data Warehouse Maintenance
- Updating large fact tables
- Refreshing aggregates
🔹 Index Creation
- Faster index building on large datasets
🔹 Data Migration
- Bulk data transfer between systems
🔹 Reporting Systems
- Updating reporting tables
- Generating summaries
👉 These operations now run faster and more efficiently.
Best Practices
To maximize benefits:
✔️ Enable Only When Needed
- Avoid unnecessary parallelism
✔️ Monitor Resource Usage
- Parallel operations use more CPU and memory
✔️ Use Appropriate Degree of Parallelism
- Balance performance vs system load
✔️ Test in Real Workloads
- Measure impact before production
Common Mistakes to Avoid
- ❌ Forgetting to enable Parallel DML
- ❌ Using unsupported table types
- ❌ Overloading system resources
- ❌ Ignoring locking behavior
Final Thoughts
Oracle 23c’s Unrestricted Parallel DML is a major step forward in database performance and usability.
✔️ Key Takeaways:
- Removes “one touch” limitation
- Allows multiple operations in same transaction
- Reduces commit overhead
- Improves performance and scalability
👉 With these enhancements, Oracle makes it easier than ever to handle large-scale data processing efficiently.
