1. In Memory OLTP
Not Just for OLTP

2. Russ Thomas Twitter: @SQLJudo Blog: www.sqljudo.com
Plural Sight: coming soon !
2 |
4/23/2019 |
@SQLJudo - Russ Thomas DBA

3. Drawbacks of Memory Expensive Volatile Precious Local
Not a file system

4. Benefits of Memory
Fast

5. In Memory OLTP (“hekaton”)
MAGIC UNICORN VERSION WAS ALREADY TAKEN BY APPLE

6. Limitations (just a few)
< 250GB (durable tables -> log is going to be disk based)
< 8060 byte row
No unique indexes
No calculated columns
No foreign keys
No partitioning
No check constraints
No alter statements
No table locks
No truncate
Non integer indexes must be binary collation
No adding indexes after creation
Row versioning protects data, true collisions generate error

7. Why OLTP Size Concurrency Speed < 250GB No Locks (row versioning)
Reads and Writes

8. Why not staging tables ??? Size ( > 250GB schema only tables )
Heaps
No constraints
No foreign keys
No indexes
No alters

9. LIVE DEMO

10. Variables to Consider Memory Limit Storage Sub-structure
Multi-threading / CPU cores
# of Transformations
Memory Limit
Running out of memory is bad
Storage Sub-structure
PCIe vs Spinning Disks vs SSD
Multi-threading / CPU cores
Serial workloads to stay under memory limit may or may not be faster than parallel work loads from disk

11. But wait, there’s more Natively Compiled Objects Hash Indexes
Columnstore Indexes coming !!

12. Russ Thomas Twitter: @SQLJudo Blog: www.sqljudo.com
Plural Sight: coming soon !
12 |
4/23/2019 |
@SQLJudo - Russ Thomas DBA