Database Reference
In-Depth Information
Online Transaction Processing
(Operational System)
Online Analytical Processing
(Analytical System, also known
as the data warehouse)
Source of
data
Operational data; OLTPs are the
original source of the data
Consolidation data; OLAP data
comes from the various OLTP
databases
Purpose of
data
To control and run fundamental
business tasks
To help with planning, problem
solving, and decision support
What the data
provides
Reveals a snapshot of ongoing
business processes
Multidimensional views of various
kinds of business activities
Inserts and
updates
Short and fast inserts and updates
initiated by end users
Periodic long-running batch jobs
refresh the data
Queries
Relatively standardized and
simple queries returning
relatively few records
Often complex queries involving
aggregations
Processing
speed
Typically very fast
Depends on the amount of data
involved; batch data refreshes and
complex queries may take many
hours
Space
requirements
Can be relatively small if
historical data is archived
Larger due to the existence of
aggregation structures and history
data; requires more indexes than
OLTP
Database
design
Highly normalized with many
tables
Typically de-normalized with fewer
tables;useofstarand/orsnowflake
schemas
Backup and
recovery
Backs up religiously; operational
data is critical to run the business,
data loss is likely to entail
significant monetary loss and
legal liability
Instead of regular backups, some
environments may consider simply
reloading the OLTP data as a
recovery method
At the time of writing this, Neo4j is clearly in the OLTP side of the database
ecosystem. That does not mean that you cannot do any analytical tasks with Neo4j.
Infact,someanalyticaltasksintherelationalworldarefarmoreeficientlyrun
on a graph database (see the sweet spot query section that follows later), but it is
not optimized for it. Typical Neo4j implementation recommendations would also
suggest that you put aside a separate Neo4j instance for these analytical workloads
so that it would not impact your production OLTP queries. In the future, Neo
Technology plans to make further enhancements to Neo4j that make it even more
suited for OLAP tasks.
