So you need to combine data from multiple tables or queries in SQL. Great news – UNION and UNION ALL make it easy! But with frustratingly similar names, it can be confusing to choose one or the other. In this guide, I‘ll demystify their key differences and show you exactly when to use each operator.
Here‘s a Quick Recap: What Do They Do?
First, let‘s review what each one does:
UNION: Combines multiple result sets and removes any duplicate rows
UNION ALL: Also combines multiple result sets but keeps all rows, with duplicates included
Pretty simple right? But there are some additional considerations that determine which one is better for your needs…
Handling Duplicates: The Key Decision Point
The core difference comes down to how UNION and UNION ALL handle duplicate values across the combined result sets:
- UNION removes any duplicate rows
- UNION ALL keeps duplicate rows
This has big implications in areas like:
- Accuracy of result set
- Performance
- Required downstream deduplication
And guides the best uses cases for each, which we‘ll explore next…
When Should I Use UNION?
UNION shines in scenarios where getting clean, distinct values is critical. For example:
- Consolidating data from related tables – Using UNION avoids overcounting rows during joins of tables with shared data
- Eliminating overlapping records from complex filters – Ensures your result set doesn‘t double-up on matching values
- Analyzing unique values across queries – Essential for accurate metrics on distinct counts, percentages, etc.
UNION also helps minimize redundant data transfer over the network and unnecessary processing. This makes it ideal for data integration and analytics pipelines.
However, there are times you may specifically want those duplicate values instead…
When UNION ALL Does the Trick
Since UNION ALL keeps all rows as-is, it works nicely when:
- You need 100% raw data from multiple sources – No duplication removal means no risk of losing rows
- Performance with very large data is critical – Way faster since it skips duplicate checks
- You know upfront there are no duplicates – Avoid spending cycles on duplicate removal
UNION ALL also makes it easy to pre-sort each individual result set using ORDER BY before consolidating everything. This level of control can be handy for transforming messy data.
Now that you know when to use each one, let‘s look at some more nitty-gritty differences…
Under the Hood: Key Technical Considerations
While UNION vs UNION ALL seem similar on the surface, going deeper reveals some noteworthy technical distinctions:
Performance
- UNION slower due to duplicate removal overhead
- UNION ALL faster since it skips duplicate handling entirely
Result Set Size
- UNION smaller result sets as dups are removed
- UNION ALL larger results since all rows are kept
NULL Handling
- UNION removes rows with NULLS matching other rows
- UNION ALL keeps all rows with NULL values
Sorting
- UNION only allows ORDER BY on final result
- UNION ALL can order individual AND final result sets
As you can see, UNION vs UNION ALL have slightly different technical charactersitics to keep in mind. You‘ll need to assess your specific needs and data to determine the best fit.
Now let‘s look at some examples in action…
UNION vs UNION ALL Example
Consider two simple tables, Table1 and Table2:
Table1
| Column1 |
|---|
| A |
| B |
Table2
| Column2 |
|---|
| B |
| C |
And the following basic query:
SELECT Column1 FROM Table1
UNION/UNION ALL
SELECT Column2 FROM Table2; If we use UNION on these tables, the result would be:
A
B
CBut with UNION ALL, we would get:
A
B
B
CYou can clearly see how UNION removed the duplicate "B" row while UNION ALL retained both.
This simple example illustrates the core duplicate handling difference – but the impacts can be even more profound on larger, complex datasets.
On that note let‘s talk performance…
Benchmarking UNION vs UNION ALL Performance
Beyond duplicate handling, one of the biggest considerations with UNION vs UNION ALL is performance. After all, slow queries can cripple production systems.
Based on benchmarks using real databases, UNION ALL consistently outperforms UNION – often by 100-1000x:
Chart showing drastic performance difference on sample database (Source: SQLPerfTips)
However, performance gaps do close as the data size and number of duplicates declines.
In other words, don’t blindly assume UNION ALL is always faster. Testing with your actual data is key.
Additionally, while UNION ALL queries may execute faster, the end result could require additional storage, memory, downstream processing, etc. due to higher row counts.
Bottom line – you need to assess both query speed AND total resource utilization when choosing between the two.
Best Practices for UNION and UNION ALL
Based on some key functional and performance differences covered, what are some best practices for using UNION vs UNION ALL effectively?
Use UNION when you need to:
- Retrieve clean, distinct values across multiple tables
- Avoid overcounting rows during complex joins or transformations
- Calculate accurate analytics on unique values
Use UNION ALL when you need to:
- Combine raw data from multiple places as-is
- Prioritize query performance over duplicate handling
- Pre-sort individual result sets before consolidating
And for both:
- Always match column counts and data types
- Test performance using data volumes in production
- Analyze impact on infrastructure beyond just query times
Sticking to these simple guidelines will help ensure you get accurate results and decent performance!
Key Takeaways: Think Distinct vs Raw Speed
When working with multiple result sets, UNION and UNION ALL make the consolidation simple. But which one to use depends on your priorities:
Choose UNION when getting clean, distinct values is critical.
Choose UNION ALL when raw speed and completeness is essential.
Beyond duplicates, also consider the performance, infrastructure needs and ordering flexibility provided by each.
And remember – the best option can depend on your actual query patterns, data volumes and infrastructure. So be sure to test with production-grade environments first before rolling out!
I hope this guide has shed some light on these very similar but importantly unique SQL operators. Now that you know UNION vs UNION ALL inside out, happy data wrangling!
