Actually, both are winners.
They both offer schemaless (schema flexibility) storage of log records, which is essential for maintaining the integrity of event logs.
In addition, they both perform well when querying date/time ranges of time-series data.
However, each database engine has its area of expertise, which became evident during our performance testing.
For example, if data ingestion rates are a problem in your enterprise, Raijin is the better choice for collecting and managing your logs.
Also, Raijin’s performance with actual aggregation queries that involve a
GROUP BY clause is phenomenal.
So, if real-time data analytics is your goal, you will be better served using Raijin for that task.
Elasticsearch still reigns as the king of full-text search in the world of database engines.
If full-text search performance is your most important feature, then you are probably already using Elasticsearch and should stick with it if that is your highest priority.
For most use cases, Raijin’s full-text search performance is acceptable.
However, the need to perform full-text searches will be significantly diminished when paired with NXLog’s powerful parsing capabilities.
This is especially true once NXLog has parsed catch-all fields used for storing embedded but flattened, structured data and has sent these new fields to Raijin as dedicated columns in a flexible schema.
Ideally, most log data should be parsed as structured data.
The need for excessive full-text searches is often an indicator of a data model that could use some design improvements.
If you are unaware of this, Raijin offers a perk that you might find very appealing.
Raijin can be downloaded for free and used as an on-premise database engine, meaning you are free to deploy it anywhere you like, and you can manage your logs without any subscription or data storage costs.