Skip to main content

Evaluating the Benefits of Sharding

Evaluating the Benefits of Sharding

InterSystems IRIS sharding can benefit a wide range of applications, but provides the greatest gains in use cases involving the following:

  • Relatively large data sets, queries that return large amounts of data, or both.

    Sharding scales caching capacity to match data size by partitioning the cache along with the data, leveraging the memory resources of multiple systems. Each data node dedicates its database cache (global buffer pool) to a fraction of the data set, as compared to a single instance’s database cache being available for all of the data. The resulting improvement becomes most evident when the data in regular use is too big to fit in the database cache of a single nonsharded instance.

  • A high volume of complex queries doing large amounts of data processing.

    Sharding scales query processing throughput by decomposing queries and executing them in parallel across multiple data nodes, leveraging the computing resources of multiple systems. The resulting improvement is most evident when queries against the cluster:

    • Read large amounts of data from persistent storage, and in particular have a high ratio of data retrieved to results returned.

    • Involve significant compute work (including aggregation, grouping, and sorting)

  • High-volume or high-speed data ingestion, or a combination.

    Sharding scales data ingestion through the InterSystems IRIS JDBC driver’s use of direct connections to the data nodes for parallel loading, distributing ingestion across multiple instances. If the data can be assumed to be validated and uniqueness checking omitted, gains are enhanced.

Each of these factors on its own influences the potential gain from sharding, but the benefit may be enhanced where they combine. For example, a combination of large amounts of data ingested quickly, large data sets, and complex queries that retrieve and process a lot of data makes many of today’s analytic workloads very good candidates for sharding.

As previously noted, and discussed in more detail in Planning an InterSystems IRIS Sharded Cluster, combining InterSystems IRIS sharding with the use of vertical scaling to address some of the factors described in the foregoing may be most beneficial under many circumstances.


In the current release, sharding does not support workloads involving complex transactions requiring atomicity, and a sharded cluster cannot be used for such workloads.

FeedbackOpens in a new tab