Monitoring performance by using the Query Store
Applies to: SQL Server 2016 (13.x) and later Azure SQL Database Azure SQL Managed Instance Azure Synapse Analytics
The SQL Server Query Store feature provides you with insight on query plan choice and performance. It simplifies performance troubleshooting by helping you quickly find performance differences caused by query plan changes. Query Store automatically captures a history of queries, plans, and runtime statistics, and retains these for your review. It separates data by time windows so you can see database usage patterns and understand when query plan changes happened on the server. You can configure query store using the ALTER DATABASE SET option.
For information about operating the Query Store in Azure SQL Database, see Operating the Query Store in Azure SQL Database.
If you are using Query Store for just in time workload insights in SQL Server 2016 (13.x), plan to install the performance scalability fixes in KB 4340759 as soon as possible.
Enabling the Query Store
Query Store is not enabled by default for new SQL Server and Azure Synapse Analytics databases, and is enabled by default for new Azure SQL Database databases.
Use the Query Store Page in SQL Server Management Studio
In Object Explorer, right-click a database, and then select Properties.
Requires at least version 16 of Management Studio.
In the Database Properties dialog box, select the Query Store page.
In the Operation Mode (Requested) box, select Read Write.
Use Transact-SQL Statements
ALTER DATABASE statement to enable the query store for a given database. For example:
ALTER DATABASE <database_name> SET QUERY_STORE = ON (OPERATION_MODE = READ_WRITE);
For more syntax options related to the Query Store, see ALTER DATABASE SET Options (Transact-SQL).
Query Store cannot be enabled for the
For information on enabling Query Store and keeping it adjusted to your workload, refer to Best Practice with the Query Store.
Information in the Query Store
Execution plans for any specific query in SQL Server typically evolve over time due to a number of different reasons such as statistics changes, schema changes, creation/deletion of indexes, etc. The procedure cache (where cached query plans are stored) only stores the latest execution plan. Plans also get evicted from the plan cache due to memory pressure. As a result, query performance regressions caused by execution plan changes can be non-trivial and time consuming to resolve.
Since the Query Store retains multiple execution plans per query, it can enforce policies to direct the Query Processor to use a specific execution plan for a query. This is referred to as plan forcing. Plan forcing in Query Store is provided by using a mechanism similar to the USE PLAN query hint, but it does not require any change in user applications. Plan forcing can resolve a query performance regression caused by a plan change in a very short period of time.
Query Store collects plans for DML Statements such as SELECT, INSERT, UPDATE, DELETE, MERGE, and BULK INSERT.
Query Store does not collect data for natively compiled stored procedures by default. Use sys.sp_xtp_control_query_exec_stats to enable data collection for natively compiled stored procedures.
Wait stats are another source of information that helps to troubleshoot performance in the Database Engine. For a long time, wait statistics were available only on instance level, which made it hard to backtrack waits to a specific query. Starting with SQL Server 2017 (14.x) and Azure SQL Database, Query Store includes a dimension that tracks wait stats. The following example enables the Query Store to collect wait stats.
ALTER DATABASE <database_name> SET QUERY_STORE = ON ( WAIT_STATS_CAPTURE_MODE = ON );
Common scenarios for using the Query Store feature are:
- Quickly find and fix a plan performance regression by forcing the previous query plan. Fix queries that have recently regressed in performance due to execution plan changes.
- Determine the number of times a query was executed in a given time window, assisting a DBA in troubleshooting performance resource problems.
- Identify top n queries (by execution time, memory consumption, etc.) in the past x hours.
- Audit the history of query plans for a given query.
- Analyze the resource (CPU, I/O, and Memory) usage patterns for a particular database.
- Identify top n queries that are waiting on resources.
- Understand wait nature for a particular query or plan.
The Query Store contains three stores:
- a plan store for persisting the execution plan information.
- a runtime stats store for persisting the execution statistics information.
- a wait stats store for persisting wait statistics information.
The number of unique plans that can be stored for a query in the plan store is limited by the max_plans_per_query configuration option. To enhance performance, the information is written to the stores asynchronously. To minimize space usage, the runtime execution statistics in the runtime stats store are aggregated over a fixed time window. The information in these stores is visible by querying the Query Store catalog views.
The following query returns information about queries and plans in the Query Store.
SELECT Txt.query_text_id, Txt.query_sql_text, Pl.plan_id, Qry.* FROM sys.query_store_plan AS Pl INNER JOIN sys.query_store_query AS Qry ON Pl.query_id = Qry.query_id INNER JOIN sys.query_store_query_text AS Txt ON Qry.query_text_id = Txt.query_text_id ;
Use the Regressed Queries feature
After enabling the Query Store, refresh the database portion of the Object Explorer pane to add the Query Store section.
Select Regressed Queries to open the Regressed Queries pane in SQL Server Management Studio. The Regressed Queries pane shows you the queries and plans in the query store. Use the drop-down boxes at the top to filter queries based on various criteria: Duration (ms) (Default), CPU Time (ms), Logical Reads (KB), Logical Writes (KB), Physical Reads (KB), CLR Time (ms), DOP, Memory Consumption (KB), Row Count, Log Memory Used (KB), Temp DB Memory Used (KB), and Wait Time (ms).
Select a plan to see the graphical query plan. Buttons are available to view the source query, force and unforce a query plan, toggle between grid and chart formats, compare selected plans (if more than one is selected), and refresh the display.
To force a plan, select a query and plan, then select Force Plan. You can only force plans that were saved by the query plan feature and are still retained in the query plan cache.
Finding waiting queries
Starting with SQL Server 2017 (14.x) and Azure SQL Database, wait statistics per query over time are available in Query Store.
In Query Store, wait types are combined into wait categories. The mapping of wait categories to wait types is available in sys.query_store_wait_stats (Transact-SQL).
Select Query Wait Statistics to open the Query Wait Statistics pane in SQL Server Management Studio v18 or higher. The Query Wait Statistics pane shows you a bar chart containing the top wait categories in the Query Store. Use the drop-down at the top to select an aggregate criteria for the wait time: avg, max, min, std dev, and total (default).
Select a wait category by clicking on the bar and a detail view on the selected wait category displays. This new bar chart contains the queries that contributed to that wait category.
Use the drop-down box at the top to filter queries based on various wait time criteria for the selected wait category: avg, max, min, std dev, and total (default). Select a plan to see the graphical query plan. Buttons are available to view the source query, force, and unforce a query plan, and refresh the display.
Wait categories are combining different wait types into buckets similar by nature. Different wait categories require a different follow-up analysis to resolve the issue, but wait types from the same category lead to very similar troubleshooting experiences, and providing the affected query on top of waits would be the missing piece to complete most such investigations successfully.
Here are some examples how you can get more insights into your workload before and after introducing wait categories in Query Store:
|Previous experience||New experience||Action|
|High RESOURCE_SEMAPHORE waits per database||High Memory waits in Query Store for specific queries||Find the top memory consuming queries in Query Store. These queries are probably delaying further progress of the affected queries. Consider using MAX_GRANT_PERCENT query hint for these queries, or for the affected queries.|
|High LCK_M_X waits per database||High Lock waits in Query Store for specific queries||Check the query texts for the affected queries and identify the target entities. Look in Query Store for other queries modifying the same entity, which are executed frequently and/or have high duration. After identifying these queries, consider changing the application logic to improve concurrency, or use a less restrictive isolation level.|
|High PAGEIOLATCH_SH waits per database||High Buffer IO waits in Query Store for specific queries||Find the queries with a high number of physical reads in Query Store. If they match the queries with high IO waits, consider introducing an index on the underlying entity, in order to do seeks instead of scans, and thus minimize the IO overhead of the queries.|
|High SOS_SCHEDULER_YIELD waits per database||High CPU waits in Query Store for specific queries||Find the top CPU consuming queries in Query Store. Among them, identify the queries for which high CPU trend correlates with high CPU waits for the affected queries. Focus on optimizing those queries - there could be a plan regression, or perhaps a missing index.|
For the available options to configure Query Store parameters, see ALTER DATABASE SET options (Transact-SQL).
sys.database_query_store_options view to determine the current options of the Query Store. For more information about the values, see sys.database_query_store_options.
For examples about setting configuration options using Transact-SQL statements, see Option Management.
For Azure Synapse Analytics, the Query Store can be enabled as on other platforms but additional configuration options are not supported.
Related Views, Functions, and Procedures
View and manage Query Store through Management Studio or by using the following views and procedures.
Query Store Functions
Functions help operations with the Query Store.
Query Store Catalog Views
Catalog views present information about the Query Store.
Query Store stored procedures
Stored procedures configure the Query Store.
1 In extreme scenarios Query Store can enter an ERROR state because of internal errors. Starting with SQL Server 2017 (14.x), if this happens, Query Store can be recovered by executing the
sp_query_store_consistency_check stored procedure in the affected database. See sys.database_query_store_options for more details described in the
actual_state_desc column description.
Key Usage Scenarios
This section provides some guidelines on managing Query Store feature itself.
Query Store state
Query Store stores its data inside the user database and that is why it has size limit (configured with
MAX_STORAGE_SIZE_MB). If data in Query Store hits that limit Query Store will automatically change state from read-write to read-only and stop collecting new data.
Query sys.database_query_store_options to determine if Query Store is currently active, and whether it is currently collects runtime stats or not.
SELECT actual_state, actual_state_desc, readonly_reason, current_storage_size_mb, max_storage_size_mb FROM sys.database_query_store_options;
Query Store status is determined by the
actual_state column. If it's different than the desired status, the
readonly_reason column can give you more information. When Query Store size exceeds the quota, the feature will switch to read_only mode and provide a reason. For information on reasons, see sys.database_query_store_options (Transact-SQL).
Get Query Store options
To find out detailed information about Query Store status, execute following in a user database.
SELECT * FROM sys.database_query_store_options;
Setting Query Store interval
You can override interval for aggregating query runtime statistics (default is 60 minutes).
ALTER DATABASE <database_name> SET QUERY_STORE (INTERVAL_LENGTH_MINUTES = 15);
Arbitrary values are not allowed for
INTERVAL_LENGTH_MINUTES. Use one of the following: 1, 5, 10, 15, 30, 60, or 1440 minutes.
New value for interval is exposed through
Query Store space usage
To check current the Query Store size and limit execute the following statement in the user database.
SELECT current_storage_size_mb, max_storage_size_mb FROM sys.database_query_store_options;
If the Query Store storage is full use the following statement to extend the storage.
ALTER DATABASE <database_name> SET QUERY_STORE (MAX_STORAGE_SIZE_MB = <new_size>);
Set Query Store options
You can set multiple Query Store options at once with a single ALTER DATABASE statement.
ALTER DATABASE <database name> SET QUERY_STORE ( OPERATION_MODE = READ_WRITE, CLEANUP_POLICY = (STALE_QUERY_THRESHOLD_DAYS = 30), DATA_FLUSH_INTERVAL_SECONDS = 3000, MAX_STORAGE_SIZE_MB = 500, INTERVAL_LENGTH_MINUTES = 15, SIZE_BASED_CLEANUP_MODE = AUTO, QUERY_CAPTURE_MODE = AUTO, MAX_PLANS_PER_QUERY = 1000, WAIT_STATS_CAPTURE_MODE = ON );
For the full list of configuration options, see ALTER DATABASE SET Options (Transact-SQL).
Cleaning up the space
Query Store internal tables are created in the PRIMARY filegroup during database creation and that configuration cannot be changed later. If you are running out of space you might want to clear older Query Store data by using the following statement.
ALTER DATABASE <db_name> SET QUERY_STORE CLEAR;
Alternatively, you might want to clear up only ad-hoc query data, since it is less relevant for query optimizations and plan analysis but takes up just as much space.
Delete ad-hoc queries
This purges adhoc and internal queries from the Query Store so that the Query Store does not run out of space and remove queries we really need to track.
SET NOCOUNT ON -- This purges adhoc and internal queries from -- the Query Store in the current database -- so that the Query Store does not run out of space -- and remove queries we really need to track DECLARE @id int; DECLARE adhoc_queries_cursor CURSOR FOR SELECT q.query_id FROM sys.query_store_query_text AS qt JOIN sys.query_store_query AS q ON q.query_text_id = qt.query_text_id JOIN sys.query_store_plan AS p ON p.query_id = q.query_id JOIN sys.query_store_runtime_stats AS rs ON rs.plan_id = p.plan_id WHERE q.is_internal_query = 1 -- is it an internal query then we dont care to keep track of it OR q.object_id = 0 -- if it does not have a valid object_id then it is an adhoc query and we don't care about keeping track of it GROUP BY q.query_id HAVING MAX(rs.last_execution_time) < DATEADD (minute, -5, GETUTCDATE()) -- if it has been more than 5 minutes since the adhoc query ran ORDER BY q.query_id; OPEN adhoc_queries_cursor ; FETCH NEXT FROM adhoc_queries_cursor INTO @id; WHILE @@fetch_status = 0 BEGIN PRINT 'EXEC sp_query_store_remove_query ' + str(@id); EXEC sp_query_store_remove_query @id; FETCH NEXT FROM adhoc_queries_cursor INTO @id; END CLOSE adhoc_queries_cursor; DEALLOCATE adhoc_queries_cursor;
You can define your own procedure with different logic for clearing up data you no longer want.
The example above uses the
sp_query_store_remove_query extended stored procedure for removing unnecessary data. You can also:
sp_query_store_reset_exec_statsto clear runtime statistics for a given plan.
sp_query_store_remove_planto remove a single plan.
Performance Auditing and Troubleshooting
Query Store keeps a history of compilation and runtime metrics throughout query executions, allowing you to ask questions about your workload. The following sample queries may be helpful in your performance baseline and query performance investigation:
Last queries executed on the database
The last n queries executed on the database:
SELECT TOP 10 qt.query_sql_text, q.query_id, qt.query_text_id, p.plan_id, rs.last_execution_time FROM sys.query_store_query_text AS qt JOIN sys.query_store_query AS q ON qt.query_text_id = q.query_text_id JOIN sys.query_store_plan AS p ON q.query_id = p.query_id JOIN sys.query_store_runtime_stats AS rs ON p.plan_id = rs.plan_id ORDER BY rs.last_execution_time DESC;
Number of executions for each query:
SELECT q.query_id, qt.query_text_id, qt.query_sql_text, SUM(rs.count_executions) AS total_execution_count FROM sys.query_store_query_text AS qt JOIN sys.query_store_query AS q ON qt.query_text_id = q.query_text_id JOIN sys.query_store_plan AS p ON q.query_id = p.query_id JOIN sys.query_store_runtime_stats AS rs ON p.plan_id = rs.plan_id GROUP BY q.query_id, qt.query_text_id, qt.query_sql_text ORDER BY total_execution_count DESC;
Longest average execution time
The number of queries with the longest average execution time within last hour:
SELECT TOP 10 rs.avg_duration, qt.query_sql_text, q.query_id, qt.query_text_id, p.plan_id, GETUTCDATE() AS CurrentUTCTime, rs.last_execution_time FROM sys.query_store_query_text AS qt JOIN sys.query_store_query AS q ON qt.query_text_id = q.query_text_id JOIN sys.query_store_plan AS p ON q.query_id = p.query_id JOIN sys.query_store_runtime_stats AS rs ON p.plan_id = rs.plan_id WHERE rs.last_execution_time > DATEADD(hour, -1, GETUTCDATE()) ORDER BY rs.avg_duration DESC;
Biggest average physical I/O reads
The number of queries that had the biggest average physical I/O reads in last 24 hours, with corresponding average row count and execution count:
SELECT TOP 10 rs.avg_physical_io_reads, qt.query_sql_text, q.query_id, qt.query_text_id, p.plan_id, rs.runtime_stats_id, rsi.start_time, rsi.end_time, rs.avg_rowcount, rs.count_executions FROM sys.query_store_query_text AS qt JOIN sys.query_store_query AS q ON qt.query_text_id = q.query_text_id JOIN sys.query_store_plan AS p ON q.query_id = p.query_id JOIN sys.query_store_runtime_stats AS rs ON p.plan_id = rs.plan_id JOIN sys.query_store_runtime_stats_interval AS rsi ON rsi.runtime_stats_interval_id = rs.runtime_stats_interval_id WHERE rsi.start_time >= DATEADD(hour, -24, GETUTCDATE()) ORDER BY rs.avg_physical_io_reads DESC;
Queries with multiple plans
These queries are especially interesting because they are candidates for regressions due to plan choice change. The following query identifies these queries along with all plans:
WITH Query_MultPlans AS ( SELECT COUNT(*) AS cnt, q.query_id FROM sys.query_store_query_text AS qt JOIN sys.query_store_query AS q ON qt.query_text_id = q.query_text_id JOIN sys.query_store_plan AS p ON p.query_id = q.query_id GROUP BY q.query_id HAVING COUNT(distinct plan_id) > 1 ) SELECT q.query_id, object_name(object_id) AS ContainingObject, query_sql_text, plan_id, p.query_plan AS plan_xml, p.last_compile_start_time, p.last_execution_time FROM Query_MultPlans AS qm JOIN sys.query_store_query AS q ON qm.query_id = q.query_id JOIN sys.query_store_plan AS p ON q.query_id = p.query_id JOIN sys.query_store_query_text qt ON qt.query_text_id = q.query_text_id ORDER BY query_id, plan_id;
Highest wait durations
This query will return top 10 queries with the highest wait durations:
SELECT TOP 10 qt.query_text_id, q.query_id, p.plan_id, sum(total_query_wait_time_ms) AS sum_total_wait_ms FROM sys.query_store_wait_stats ws JOIN sys.query_store_plan p ON ws.plan_id = p.plan_id JOIN sys.query_store_query q ON p.query_id = q.query_id JOIN sys.query_store_query_text qt ON q.query_text_id = qt.query_text_id GROUP BY qt.query_text_id, q.query_id, p.plan_id ORDER BY sum_total_wait_ms DESC
Queries that recently regressed in performance
The following query example returns all queries for which execution time doubled in last 48 hours due to a plan choice change. This query compares all runtime stat intervals side by side:
SELECT qt.query_sql_text, q.query_id, qt.query_text_id, rs1.runtime_stats_id AS runtime_stats_id_1, rsi1.start_time AS interval_1, p1.plan_id AS plan_1, rs1.avg_duration AS avg_duration_1, rs2.avg_duration AS avg_duration_2, p2.plan_id AS plan_2, rsi2.start_time AS interval_2, rs2.runtime_stats_id AS runtime_stats_id_2 FROM sys.query_store_query_text AS qt JOIN sys.query_store_query AS q ON qt.query_text_id = q.query_text_id JOIN sys.query_store_plan AS p1 ON q.query_id = p1.query_id JOIN sys.query_store_runtime_stats AS rs1 ON p1.plan_id = rs1.plan_id JOIN sys.query_store_runtime_stats_interval AS rsi1 ON rsi1.runtime_stats_interval_id = rs1.runtime_stats_interval_id JOIN sys.query_store_plan AS p2 ON q.query_id = p2.query_id JOIN sys.query_store_runtime_stats AS rs2 ON p2.plan_id = rs2.plan_id JOIN sys.query_store_runtime_stats_interval AS rsi2 ON rsi2.runtime_stats_interval_id = rs2.runtime_stats_interval_id WHERE rsi1.start_time > DATEADD(hour, -48, GETUTCDATE()) AND rsi2.start_time > rsi1.start_time AND p1.plan_id <> p2.plan_id AND rs2.avg_duration > 2*rs1.avg_duration ORDER BY q.query_id, rsi1.start_time, rsi2.start_time;
If you want to see performance all regressions (not only those related to plan choice change) than just remove condition
AND p1.plan_id <> p2.plan_id from the previous query.
Queries with historical regression in performance
Comparing recent execution to historical execution, the next query compares query execution based periods of execution. In this particular example, the query compares execution in recent period (1 hour) vs. history period (last day) and identifies those that introduced
additional_duration_workload. This metric is calculated as a difference between recent average execution and history average execution multiplied by the number of recent executions. It actually represents how much of additional duration recent executions introduced compared to history:
--- "Recent" workload - last 1 hour DECLARE @recent_start_time datetimeoffset; DECLARE @recent_end_time datetimeoffset; SET @recent_start_time = DATEADD(hour, -1, SYSUTCDATETIME()); SET @recent_end_time = SYSUTCDATETIME(); --- "History" workload DECLARE @history_start_time datetimeoffset; DECLARE @history_end_time datetimeoffset; SET @history_start_time = DATEADD(hour, -24, SYSUTCDATETIME()); SET @history_end_time = SYSUTCDATETIME(); WITH hist AS ( SELECT p.query_id query_id, ROUND(ROUND(CONVERT(FLOAT, SUM(rs.avg_duration * rs.count_executions)) * 0.001, 2), 2) AS total_duration, SUM(rs.count_executions) AS count_executions, COUNT(distinct p.plan_id) AS num_plans FROM sys.query_store_runtime_stats AS rs JOIN sys.query_store_plan AS p ON p.plan_id = rs.plan_id WHERE (rs.first_execution_time >= @history_start_time AND rs.last_execution_time < @history_end_time) OR (rs.first_execution_time <= @history_start_time AND rs.last_execution_time > @history_start_time) OR (rs.first_execution_time <= @history_end_time AND rs.last_execution_time > @history_end_time) GROUP BY p.query_id ), recent AS ( SELECT p.query_id query_id, ROUND(ROUND(CONVERT(FLOAT, SUM(rs.avg_duration * rs.count_executions)) * 0.001, 2), 2) AS total_duration, SUM(rs.count_executions) AS count_executions, COUNT(distinct p.plan_id) AS num_plans FROM sys.query_store_runtime_stats AS rs JOIN sys.query_store_plan AS p ON p.plan_id = rs.plan_id WHERE (rs.first_execution_time >= @recent_start_time AND rs.last_execution_time < @recent_end_time) OR (rs.first_execution_time <= @recent_start_time AND rs.last_execution_time > @recent_start_time) OR (rs.first_execution_time <= @recent_end_time AND rs.last_execution_time > @recent_end_time) GROUP BY p.query_id ) SELECT results.query_id AS query_id, results.query_text AS query_text, results.additional_duration_workload AS additional_duration_workload, results.total_duration_recent AS total_duration_recent, results.total_duration_hist AS total_duration_hist, ISNULL(results.count_executions_recent, 0) AS count_executions_recent, ISNULL(results.count_executions_hist, 0) AS count_executions_hist FROM ( SELECT hist.query_id AS query_id, qt.query_sql_text AS query_text, ROUND(CONVERT(float, recent.total_duration/ recent.count_executions-hist.total_duration/hist.count_executions) *(recent.count_executions), 2) AS additional_duration_workload, ROUND(recent.total_duration, 2) AS total_duration_recent, ROUND(hist.total_duration, 2) AS total_duration_hist, recent.count_executions AS count_executions_recent, hist.count_executions AS count_executions_hist FROM hist JOIN recent ON hist.query_id = recent.query_id JOIN sys.query_store_query AS q ON q.query_id = hist.query_id JOIN sys.query_store_query_text AS qt ON q.query_text_id = qt.query_text_id ) AS results WHERE additional_duration_workload > 0 ORDER BY additional_duration_workload DESC OPTION (MERGE JOIN);
Maintaining query performance stability
For queries executed multiple times you may notice that SQL Server uses different plans, resulting in different resource utilization and duration. With Query Store, you can detect when query performance regressed and determine the optimal plan within a period of interest. You can then force that optimal plan for future query execution.
You can also identify inconsistent query performance for a query with parameters (either auto-parameterized or manually parameterized). Among different plans you can identify the plan that is fast and optimal enough for all or most of the parameter values and force that plan, keeping predictable performance for the wider set of user scenarios.
Force a plan for a query (apply forcing policy)
When a plan is forced for a certain query, SQL Server tries to force the plan in the optimizer. If plan forcing fails, an XEvent is fired and the optimizer is instructed to optimize in the normal way.
EXEC sp_query_store_force_plan @query_id = 48, @plan_id = 49;
sp_query_store_force_plan you can only force plans that were recorded by Query Store as a plan for that query. In other words, the only plans available for a query are those that were already used to execute that query while Query Store was active.
Starting with SQL Server 2019 (15.x) and Azure SQL Database (all deployment models), Query Store supports the ability to force query execution plans for fast forward and static Transact-SQL and API cursors. Forcing is supported via
sp_query_store_force_plan or through SQL Server Management Studio Query Store reports.
Remove plan forcing for a query
To rely again on the SQL Server query optimizer to calculate the optimal query plan, use
sp_query_store_unforce_plan to unforce the plan that was selected for the query.
EXEC sp_query_store_unforce_plan @query_id = 48, @plan_id = 49;
- Best Practice with the Query Store
- Using the Query Store with In-Memory OLTP
- Query Store Usage Scenarios
- How Query Store Collects Data
- Query Store Stored Procedures (Transact-SQL)
- Query Store Catalog Views (Transact-SQL)
- Monitor and Tune for Performance
- Performance Monitoring and Tuning Tools
- Open Activity Monitor (SQL Server Management Studio)
- Live Query Statistics
- Activity Monitor
- sys.database_query_store_options (Transact-SQL)