In our previous deep dives, we learned how to capture slow queries using Extended Events and how to diagnose them manually using Execution Plans. But there is one major problem with these manual methods: They only tell you what is happening right now.
If an application owner calls you at 9:00 AM on a Monday and says, "The database was incredibly slow yesterday at 3:00 PM," traditional tools won't help much. Unless you were actively running a trace at that exact moment, that performance data is gone forever once the plan is evicted from memory.
To solve this, Microsoft introduced Query Store. Think of Query Store as the "Flight Data Recorder" (the Black Box) for your database. It automatically captures a history of every query, every execution plan, and every runtime statistic, persisting them safely to disk. Let's explore the beautiful internal architecture of Query Store and learn how to use it to reverse performance regressions with a single click.
1. The Real-World Analogy: The Recording Studio
To understand the Query Store architecture, imagine a high-end music recording studio.
The Live Performance (The Query): The musicians (applications) are playing music (running queries) in real-time.
The Mixing Desk (The Plan Store): Every time a new song is played, the sound engineer records the exact settings and "recipe" used to make it sound good.
The Logs (Runtime Stats): A computer tracks how long the song lasted, how much power the speakers used, and if there were any technical glitches.
The Archive (The Disk Storage): Instead of throwing these notes away after the concert, the studio saves every single recording and setting into a permanent vault so they can be reviewed months later.
2. Diagram 1: The Three Pillars of Query Store Data
Query Store doesn't just save one thing; it manages three distinct buckets of information that work together to give you the "Full Picture" of database health.
3. Under the Hood: The Asynchronous Architecture
One of the biggest concerns for a Junior DBA is: "Will enabling Query Store slow down my production server?"
The answer is No, thanks to its brilliant asynchronous design. Query Store is built to be "Performance Neutral."
Capture: When a query runs, the data is first captured in a very fast In-Memory buffer. This happens in real-time but has almost zero impact on the query's execution.
Asynchronous Write: A background system task periodically wakes up and flushes the data from the memory buffers to the physical system tables inside your database.
Efficiency: If the server is under extreme stress, Query Store can even "throttle" itself to ensure it never steals resources from your primary application traffic.
4. Diagram 2: The Data Collection Pipeline
Visualizing the journey from an active query to a permanent record on disk helps conceptualize how SQL Server protects your performance.
5. The "Aha!" Moment: Fixing Plan Regression
The most powerful feature of Query Store is its ability to detect Plan Regression. This happens when a query that used to be fast suddenly becomes slow—usually because the Optimizer picked a "bad" execution plan (like an Index Scan instead of a Seek) due to a parameter change.
Before Query Store, you had to manually find the query, find the old plan, and use a PLAN HINT in your code to fix it. With Query Store, you can simply compare the "Good" plan to the "Bad" plan and click "Force Plan."
6. Practical T-SQL: Enabling and Querying the Store
Enabling Query Store
By default, Query Store is OFF on older versions but ON by default in SQL Server 2022. You should always configure it to ensure it doesn't grow too large:
ALTER DATABASE [YourDatabaseName] SET QUERY_STORE = ON (
OPERATION_MODE = READ_WRITE,
CLEANUP_POLICY = (STALE_QUERY_THRESHOLD_DAYS = 30), -- Keep 30 days of history
DATA_FLUSH_INTERVAL_SECONDS = 900, -- Flush to disk every 15 mins
MAX_STORAGE_SIZE_MB = 1000, -- Limit storage to 1GB
INTERVAL_LENGTH_MINUTES = 60 -- Aggregate data into 1-hour buckets
);
GO
Finding Your "Top 5" Resource Hogs
Instead of waiting for a user to complain, you can use Query Store's metadata views to find the most expensive queries that have run over the last 24 hours:
SELECT TOP 5
q.query_id,
st.query_sql_text,
CAST(rs.avg_duration / 1000.0 AS DECIMAL(10,2)) AS [Avg_Duration_MS],
rs.count_executions,
rs.avg_cpu_time / 1000.0 AS [Avg_CPU_MS],
rs.avg_logical_io_reads AS [Avg_Logical_Reads]
FROM sys.query_store_query q
JOIN sys.query_store_query_text st ON q.query_text_id = st.query_text_id
JOIN sys.query_store_plan p ON q.query_id = p.query_id
JOIN sys.query_store_runtime_stats rs ON p.plan_id = rs.plan_id
WHERE rs.last_execution_time > DATEADD(hour, -24, GETDATE())
ORDER BY rs.avg_duration DESC;
Analyzing Why Queries are Waiting
Starting in SQL Server 2017+, Query Store also captures Wait Stats. This tells you why a query was slow (e.g., waiting on a lock or waiting on the disk):
SELECT
ws.wait_category_desc,
ws.total_query_wait_time_ms,
ws.avg_query_wait_time_ms,
st.query_sql_text
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 st ON q.query_text_id = st.query_text_id
WHERE ws.execution_type = 0 -- Regular executions
ORDER BY ws.total_query_wait_time_ms DESC;
7. The Junior DBA Triage Summary
Query Store is your ultimate safety net. It allows you to:
Travel Back in Time: See exactly how a query performed yesterday, last week, or last month.
Fix Regressions Instantly: Use "Force Plan" to stop a production fire in seconds without changing a single line of application code.
Audit Changes: See if a recent index addition or code deployment actually helped or hurt performance.
By mastering the architecture of the Plan, Runtime, and Wait stores, you transition from a "reactive" DBA who fixes things after they break, to a "proactive" architect who maintains a perfectly tuned, stable environment.
Have you used Query Store to track down a "hidden" performance regression in your environment? Do you prefer the SSMS GUI reports or writing custom DMV queries to find your bottlenecks? Let's discuss in the comments below!
