> ## Documentation Index
> Fetch the complete documentation index at: https://docs.startree.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Release Version 0.7.0: August 2023

## Apache Pinot updates since last StarTree release

* Delete records in upsert-enabled tables
* Pipeline breaker and dynamic broadcast support for semi-joins
* Null value support in aggregate and filters
* Order null values
* Support `UNION`, `INTERSECT`, and `EXCEPT` operators
* Support ranking window functions for v2 engine:
  * `ROW_NUMBER` window function support
  * `RANK`
  * `DENSE_RANK`
* Multistage query updates:
  * Table-level access validation
  * Queries per second (QPS) quota check for all tables
  * Phase timers for `REQUEST_COMPILATION`, `AUTHORIZATION`, and `QUERY_EXECUTION`

## StarTree Cloud

The following updates apply to both bring-your-own-cloud (BYOC) and SaaS deployments.

* Configure tags to add to all StarTree-managed AWS resources, which can be useful for auditing and compliance initiatives.
* StarTree's Pinot deep store S3 bucket has additional default protections. The bucket policy now actively denies any non-SSL traffic.
* All new and existing clusters will be upgraded to use Kubernetes version 1.24.
* StarTree-provisioned Google Cloud Platorm (GCP) clusters are now VPC-native. Specify subnet CIDRs for nodes, pods, and services.
* We've added automated certification renewal to TLS certiticates to improve the architecture's stability and reliability.
* In a disaster, recover a workspace in from a region failure by recovering the StarTree cluster state.
* Administrators can release individual components, like Pinot or Data Manager, without requiring a full release.

### StarTree extensions for Apache Pinot

* Delete selected records from a Pinot table to meet GDPR requirements. See [Segment purge](/corecapabilities/manage-data/purge-task) for details.

#### Beta extensions

* *(BETA)* Pinot server restart time is optimized for large upsert-enabled tables.
* *(BETA)* Tiered storage:
* Tiered storage supports sparse indexes, leading to performance improvements for queries running against high cardinality columns. For details, see [Use sparse index](/corecapabilities/manage-data/set-up-tiered-storage/use-sparse-index)
* Google Cloud Services (GCS) is available as a cloud tier.
* Stale segments are automatically cleaned up from the object tier.
* Trace remote reads with newly available statistics.
* Overwrite index configurations for the object tier.

#### Alpha extensions

* *(ALPHA)* Push data into Pinot to create a table with the write API. Send data from any application to a REST API endpoint.

## Data Manager

* Data Manager now masks connection credentials to improve security.
* We've optimized minion segment creation to avoid out-of-memory (OOM) and out-of-disk (OOD) issues during ingestion, increasing batch ingestion reliability.
* The segment refresh task is more stable and reliabile when users change table configuration of an existing table.
* Integrate with Delta Lake and Databricks Lakehouse to ingest data and keep it in sync in Pinot.
* Configure batch ingestion to be performed atomically (either all or none of the data is ingested), preventing inconsistency in query results.
* Continuously backfill data from BigQuery with each periodic sync.
* Connect to Amazon Web Services (AWS) Kinesis and S3 using an AWS cross-account IAM role.
* Integrate with Confluent Cloud.
* *(BETA)* Backfill data from SQL sources on an ad hoc basis.

## ThirdEye

* We've simplified the workflow for creating and configuring new alerts.
* ThirdEye alerts support data mutability, meaning they can handle recent changes in underlying data. For details, see [Streaming upsert use case](/thirdeye/concepts-data-alerts-notifications/concepts-mutable-data).
* Configure subscription groups on a per-dimension basis within an alert to alert specific teams to for anomalies in different slices of the underlying dataset. For details, see [Create a subscription group](/thirdeye/how-tos/add_notification).
* Filter and sort dimensions by name and latest anomaly from the UI. We've also improve performance for dimension exploration.
* Anomaly detector algorithm updates:
  * [Exponential smoothing (ETS)](/thirdeye/operators/anomaly-detector/ets) performance has improved.
  * Find anomalies in seasonal patterns with the new [Matrix profile algorithm](/thirdeye/operators/anomaly-detector/matrix_profile).
* [Default alert templates](/thirdeye/how-tos/alert/use-templates) are now automatically refreshed on new releases instead of requiring an API request.


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.