About experimental features
Imply Long Term Support (LTS) releases and Short Term Support (STS) releases include experimental features that are at one of two possible lifecycle stages:
Alpha: An alpha feature may include major bugs or performance issues. It may also be otherwise feature-limited. Alpha features are not ready for production use, but are instead suitable for feature previews and learning environments.
Alpha features may be subject to significant changes or removal without prior notice.
Beta: Beta features should be suitable for production scenarios. However, you should only enable a beta feature after testing in a staging environment. When you feel comfortable to move to production, enable beta features in closely-monitored scenarios.
Imply Druid experimental features
For experimental Imply Druid features, refer to individual feature documentation for instructions to enable the feature.
Experimental features in Imply's distribution of Druid include:
- Apache Kafka extraction namespace
- Avro extension
- Bloom filter extension
- Confluent schema registry ingestion support
- Indexer process
- Indexed tables
- Enhanced query planning for correlated subqueries
- Kerberos
- Lookups
- Microsoft Azure extension
- Segment locking
- Segment-level caching on the broker
- SQL-compatible null handling
- Stats
- Whole result caching
Pivot experimental features
Experimental features can be individually enabled or disabled in the Pivot UI. See Feature flags for more information.
Experimental features in Pivot include:
- Batch dashboard updates
- Convert data cubes to SQL
- Create SQL data cubes
- CrossTab
- Embedded visualizations
- Error notifications
- Event annotations
- Explain
- Query cancellation
Imply platform experimental features
Experimental features in Imply Platform include: