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Write SQL blazing fast in an editor designed for data analysts
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Rahul Pattamatta
Administrator
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Schema
Search Tables...
category
4
catid
catgroup
catdesc
catname
date
8
dateid
caldate
day
month
week
qtr
holiday
year
event
4
dateid
catid
venueid
eventid
starttime
listing
8
category
4
SQL Editor
dbn s3
(s3)
Format
Run Query
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event_metrics AS (
SELECT
person_id,
distinct_id,
FROM event_base
GROUP BY distinct_id, person_id
)
COUNT(DISTINCT uuid) AS total_events,
COUNT(DISTINCT event) AS unique_event_types,
COUNT(DISTINCT event_date) AS active_days,
MIN(timestamp) AS first_event_time,
MAX(timestamp) AS last_event_time,
EXTRACT(EPOCH FROM (MAX(timestamp) - MIN(timestamp))) / 86400.0 AS days_between_first_last,
-- Additional metrics you could add:
COUNT(DISTINCT event_week) AS active_weeks,
COUNT(*) / NULLIF(COUNT(DISTINCT event_date), 0) AS avg_events_per_active_day,
MAX(timestamp): :DATE - MIN(timestamp)::DATE + 1 AS calendar_days_span
Press Cd/Ctri + Enter to run query (selection or cursor statement) • Cd/Ctri + Shift + F to format - Cmd/Ctri + / to ask in chat - Select text + Cmd/Ctri + Shift + Enter to ask Al
Charts
Results
Results
(202 Rows)
Pivot
Totals
Save as Table
VENUEID
VENUENAME
VENUECITY
VENUESTATE
TOTAL_EVENTS
TOTAL_TRANSACT
220
Nederlander Theatre
New York City
NY
81
1,456
212
Winter Garden Theatre
New York City
NY
83
1,672
222
Lunt-Fontanne Theatre
New York City
NY
82
1,532
226
Winter Garden Theatre
New York City
NY
80
1,456
220
Majestic Theatre
New York City
NY
91
1,234
225
Lunt-Fontanne Theatre
New York City
NY
81
1,583
228
August Wilson Theatre
New York City
NY
78
1,234
250
Majestic Theatre
New York City
NY
81
1,456
1-10 of 202 rows
First
Previous
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....
21
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Last
AI Assistant
Data Exploration - 11:03:33 PM
total events counts by date
Here's my approach:
Analysis
Based on your request for "total events counts by date", I'll create a query that counts the number of events grouped by date. Since we have a timestamp column in the s3_posthog_event table, I'll extract the date portion from it and group the events accordingly.
Count total events by date
11:09 PM
SQL diff compared to previous query
-- Count total events by date
SELECT
DATE(timestamp) AS event_date,
COUNT(*) AS total_events
FROM s3_posthog_events
WHERE timestamp IS NOT NULL
GROUP BY DATE(timestamp)
ORDER BY event_date DESC
LIMIT 1000;
timestamp
s3_posthog_events
Using: | Model: | Version:
|
Agent
Dashboard
Data Studio
IDE
RP
Rahul Pattamatta
Administrator
Threads
Schema
Search Tables...
category
4
catid
catgroup
catdesc
catname
date
8
dateid
caldate
day
month
week
qtr
holiday
year
event
4
dateid
catid
venueid
eventid
starttime
listing
8
category
4
SQL Editor
dbn s3
(s3)
Format
Run Query
1
2
3
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5
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event_metrics AS (
SELECT
person_id,
distinct_id,
FROM event_base
GROUP BY distinct_id, person_id
)
COUNT(DISTINCT uuid) AS total_events,
COUNT(DISTINCT event) AS unique_event_types,
COUNT(DISTINCT event_date) AS active_days,
MIN(timestamp) AS first_event_time,
MAX(timestamp) AS last_event_time,
EXTRACT(EPOCH FROM (MAX(timestamp) - MIN(timestamp))) / 86400.0 AS days_between_first_last,
-- Additional metrics you could add:
COUNT(DISTINCT event_week) AS active_weeks,
COUNT(*) / NULLIF(COUNT(DISTINCT event_date), 0) AS avg_events_per_active_day,
MAX(timestamp): :DATE - MIN(timestamp)::DATE + 1 AS calendar_days_span
Press Cd/Ctri + Enter to run query (selection or cursor statement) • Cd/Ctri + Shift + F to format - Cmd/Ctri + / to ask in chat - Select text + Cmd/Ctri + Shift + Enter to ask Al
Charts
Results
Results
(202 Rows)
Pivot
Totals
Save as Table
VENUEID
VENUENAME
VENUECITY
VENUESTATE
TOTAL_EVENTS
TOTAL_TRANSACT
220
Nederlander Theatre
New York City
NY
81
1,456
212
Winter Garden Theatre
New York City
NY
83
1,672
222
Lunt-Fontanne Theatre
New York City
NY
82
1,532
226
Winter Garden Theatre
New York City
NY
80
1,456
220
Majestic Theatre
New York City
NY
91
1,234
225
Lunt-Fontanne Theatre
New York City
NY
81
1,583
228
August Wilson Theatre
New York City
NY
78
1,234
250
Majestic Theatre
New York City
NY
81
1,456
1-10 of 202 rows
First
Previous
1
2
3
4
....
21
Next
Last
AI Assistant
Data Exploration - 11:03:33 PM
total events counts by date
Here's my approach:
Analysis
Based on your request for "total events counts by date", I'll create a query that counts the number of events grouped by date. Since we have a timestamp column in the s3_posthog_event table, I'll extract the date portion from it and group the events accordingly.
Count total events by date
11:09 PM
SQL diff compared to previous query
-- Count total events by date
SELECT
DATE(timestamp) AS event_date,
COUNT(*) AS total_events
FROM s3_posthog_events
WHERE timestamp IS NOT NULL
GROUP BY DATE(timestamp)
ORDER BY event_date DESC
LIMIT 1000;
timestamp
s3_posthog_events
Using: | Model: | Version:
|
Agent
The AI-first SQL editor
Write SQL blazing fast in an editor designed for data analysts
The AI-first SQL editor
Write SQL blazing fast in an editor designed for data analysts
BENEFITS
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Everything you need to write SQL, verify accuracy, and build insights
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Generate SQL from scratch or edit large and complex queries.
Generate SQL
Generate SQL from scratch or edit large and complex queries.
Generate SQL
Generate SQL from scratch or edit large and complex queries.
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Chat with your db
Plan tasks, ask AI about your schema, ERD and find columns.
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Plan tasks, ask AI about your schema, ERD and find columns.
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Tura automatically analyzes your SQL to surface root causes of bugs
Spot and fix bugs
Tura automatically analyzes your SQL to surface root causes of bugs
Spot and fix bugs
Tura automatically analyzes your SQL to surface root causes of bugs
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SQL Editor
dbn s3
(s3)
Format
Run Query
1
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event_metrics AS (
SELECT
person_id,
distinct_id,
FROM event_base
GROUP BY distinct_id, person_id
)
COUNT(DISTINCT uuid) AS total_events,
COUNT(DISTINCT event) AS unique_event_types,
COUNT(DISTINCT event_date) AS active_days,
MIN(timestamp) AS first_event_time,
MAX(timestamp) AS last_event_time,
EXTRACT(EPOCH FROM (MAX(timestamp) - MIN(timestamp))) / 86400.0 AS days_between_first_last,
-- Additional metrics you could add:
COUNT(DISTINCT event_week) AS active_weeks,
COUNT(*) / NULLIF(COUNT(DISTINCT event_date), 0) AS avg_events_per_active_day,
MAX(timestamp): :DATE - MIN(timestamp)::DATE + 1 AS calendar_days_span
Press Cd/Ctri + Enter to run query (selection or cursor statement) • Cd/Ctri + Shift + F to format - Cmd/Ctri + / to ask in chat - Select text + Cmd/Ctri + Shift + Enter to ask Al
SQL Editor
dbn s3
(s3)
Format
Run Query
1
2
3
4
5
6
7
8
9
10
11
12
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20
event_metrics AS (
SELECT
person_id,
distinct_id,
FROM event_base
GROUP BY distinct_id, person_id
)
COUNT(DISTINCT uuid) AS total_events,
COUNT(DISTINCT event) AS unique_event_types,
COUNT(DISTINCT event_date) AS active_days,
MIN(timestamp) AS first_event_time,
MAX(timestamp) AS last_event_time,
EXTRACT(EPOCH FROM (MAX(timestamp) - MIN(timestamp))) / 86400.0 AS days_between_first_last,
-- Additional metrics you could add:
COUNT(DISTINCT event_week) AS active_weeks,
COUNT(*) / NULLIF(COUNT(DISTINCT event_date), 0) AS avg_events_per_active_day,
MAX(timestamp): :DATE - MIN(timestamp)::DATE + 1 AS calendar_days_span
Press Cd/Ctri + Enter to run query (selection or cursor statement) • Cd/Ctri + Shift + F to format - Cmd/Ctri + / to ask in chat - Select text + Cmd/Ctri + Shift + Enter to ask Al
SQL Auto-Completion
Use tabs to autocomplete and write fully schema-aware code.
SQL Editor
dbn s3
(s3)
Format
Run Query
1
2
3
4
5
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7
8
9
10
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event_metrics AS (
SELECT
person_id,
distinct_id,
FROM event_base
GROUP BY distinct_id, person_id
)
COUNT(DISTINCT uuid) AS total_events,
COUNT(DISTINCT event) AS unique_event_types,
COUNT(DISTINCT event_date) AS active_days,
MIN(timestamp) AS first_event_time,
MAX(timestamp) AS last_event_time,
EXTRACT(EPOCH FROM (MAX(timestamp) - MIN(timestamp))) / 86400.0 AS days_between_first_last,
-- Additional metrics you could add:
COUNT(DISTINCT event_week) AS active_weeks,
COUNT(*) / NULLIF(COUNT(DISTINCT event_date), 0) AS avg_events_per_active_day,
MAX(timestamp): :DATE - MIN(timestamp)::DATE + 1 AS calendar_days_span
Press Cd/Ctri + Enter to run query (selection or cursor statement) • Cd/Ctri + Shift + F to format - Cmd/Ctri + / to ask in chat - Select text + Cmd/Ctri + Shift + Enter to ask Al
AI Assistant
Here's my approach:
I see you've selected the event_metrics CTE from your complex query. This
CTE is calculating key user-level metrics from the event data. Let me analyze
what this specific part does:
Analysis of the Selected CTE: 'event_ metrics"
What this CTE does
The event_metrics CTE aggregates event data at the user level, calculating
several important metrics:
**Total Events** ('total _events*): Counts unique event occurrences per user using ' COUNT(DISTINCT uuid) *
**Event Variety** ('unique_event_types*): Counts how many different types of events each user has triggered
**Activity Span** ('active_days*): Counts the number of distinct days a user was active
**Time Boundaries**: Captures the first and last event timestamps for each user
**User Lifetime** (*days_between_first_last*): Calculates the number of days between a user's first and last event
event_metrics
Key Design Decisions
**Grouping Strategy**: Groups by both distinct_id and person_id to maintain user identity consistency
**Time Calculation**: Uses EXTRACTEPOCH FR t convert the
event_metrics
distinct_id
person_id
EXTRACT(EPOCH FROM ...)
Using: | Model: | Version:
Generate SQL for questions like 'Find total sales by region for last month'...
Agent
SQL Editor
dbn s3
(s3)
Format
Run Query
1
2
3
4
5
6
7
8
9
10
11
12
13
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event_metrics AS (
SELECT
person_id,
distinct_id,
FROM event_base
GROUP BY distinct_id, person_id
)
COUNT(DISTINCT uuid) AS total_events,
COUNT(DISTINCT event) AS unique_event_types,
COUNT(DISTINCT event_date) AS active_days,
MIN(timestamp) AS first_event_time,
MAX(timestamp) AS last_event_time,
EXTRACT(EPOCH FROM (MAX(timestamp) - MIN(timestamp))) / 86400.0 AS days_between_first_last,
-- Additional metrics you could add:
COUNT(DISTINCT event_week) AS active_weeks,
COUNT(*) / NULLIF(COUNT(DISTINCT event_date), 0) AS avg_events_per_active_day,
MAX(timestamp): :DATE - MIN(timestamp)::DATE + 1 AS calendar_days_span
Press Cd/Ctri + Enter to run query (selection or cursor statement) • Cd/Ctri + Shift + F to format - Cmd/Ctri + / to ask in chat - Select text + Cmd/Ctri + Shift + Enter to ask Al
AI Assistant
Here's my approach:
I see you've selected the event_metrics CTE from your complex query. This
CTE is calculating key user-level metrics from the event data. Let me analyze
what this specific part does:
Analysis of the Selected CTE: 'event_ metrics"
What this CTE does
The event_metrics CTE aggregates event data at the user level, calculating
several important metrics:
**Total Events** ('total _events*): Counts unique event occurrences per user using ' COUNT(DISTINCT uuid) *
**Event Variety** ('unique_event_types*): Counts how many different types of events each user has triggered
**Activity Span** ('active_days*): Counts the number of distinct days a user was active
**Time Boundaries**: Captures the first and last event timestamps for each user
**User Lifetime** (*days_between_first_last*): Calculates the number of days between a user's first and last event
event_metrics
Key Design Decisions
**Grouping Strategy**: Groups by both distinct_id and person_id to maintain user identity consistency
**Time Calculation**: Uses EXTRACTEPOCH FR t convert the
event_metrics
distinct_id
person_id
EXTRACT(EPOCH FROM ...)
Using: | Model: | Version:
Generate SQL for questions like 'Find total sales by region for last month'...
Agent
Ask about your database
Save hours finding column names, table names and appropriate metrics.
Error: Query execution error for s3 connection 'dbn s3': Parser Error: syntax error at or near "LIMIT"
Fix in Chat
Format
Run Query
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-- Complex CTE analysis for 53 posthog events table
SELECT
-- This query demonstrates multiple CTE levels with various analytical techniques
-- This query demonstrates multiple CTE levels with various analytical techniques
WITH base_events AS (
SELECT
uuid,
timestamp,
events,
properties,
distinct_id,
person_id,
person_properties,
DATE_TRUNC(‘day’,timestamp) AS event_date,
DATE_TRUNC(‘hour’,timestamp) AS event_hour,
EXTRACT(dow FROM timestamp) AS day_of_week,
EXTRACT(hour FROM timestamp) AS hour_of_day,
1 of 1 problem
7
Query execution error for s3 connection 'dbn s3': Parser Error: syntax error at or near "LIMIT" SQL Error
Press Cd/Ctri + Enter to run query (selection or cursor statement) • Cd/Ctri + Shift + F to format - Cmd/Ctri + / to ask in chat - Select text + Cmd/Ctri + Shift + Enter to ask Al
Query execution error for s3 connection 'dbn s3": Parser Error: syntax error at or near "LIMIT"
Error: Query execution error for s3 connection 'dbn s3': Parser Error: syntax error at or near "LIMIT"
Fix in Chat
Format
Run Query
1
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-- Complex CTE analysis for 53 posthog events table
SELECT
-- This query demonstrates multiple CTE levels with various analytical techniques
-- This query demonstrates multiple CTE levels with various analytical techniques
WITH base_events AS (
SELECT
uuid,
timestamp,
events,
properties,
distinct_id,
person_id,
person_properties,
DATE_TRUNC(‘day’,timestamp) AS event_date,
DATE_TRUNC(‘hour’,timestamp) AS event_hour,
EXTRACT(dow FROM timestamp) AS day_of_week,
EXTRACT(hour FROM timestamp) AS hour_of_day,
1 of 1 problem
7
Query execution error for s3 connection 'dbn s3': Parser Error: syntax error at or near "LIMIT" SQL Error
Press Cd/Ctri + Enter to run query (selection or cursor statement) • Cd/Ctri + Shift + F to format - Cmd/Ctri + / to ask in chat - Select text + Cmd/Ctri + Shift + Enter to ask Al
Query execution error for s3 connection 'dbn s3": Parser Error: syntax error at or near "LIMIT"
Auto-fix syntax issues
No more copying CTE's, verifying them and re-running scripts.
Auto-fix syntax issues
No more copying CTE's, verifying them and re-running scripts.
Charts
Results
Results
(202 Rows)
Pivot
Totals
Save as Table
VENUENAME
VENUECITY
VENUEID
TOTAL_EVENTS
TOTAL_TRANSACT
Nederlander Theatre
New York City
220
81
1,456
Winter Garden Theatre
New York City
212
83
1,672
Lunt-Fontanne Theatre
New York City
222
82
1,532
Winter Garden Theatre
New York City
226
80
1,456
Majestic Theatre
New York City
220
91
1,234
Lunt-Fontanne Theatre
New York City
225
81
1,583
August Wilson Theatre
New York City
228
78
1,234
Majestic Theatre
New York City
250
81
1,456
1-10 of 202 rows
First
Previous
1
2
3
4
....
21
Next
Last
Column Actions
Ask AI
Sort Ascending
Sort Desceding
Filter Column
Add Column
Aggregates
Average
Count Distinct
List Values
Charts
Results
Results
(202 Rows)
Pivot
Totals
Save as Table
VENUENAME
VENUECITY
VENUEID
TOTAL_EVENTS
TOTAL_TRANSACT
Nederlander Theatre
New York City
220
81
1,456
Winter Garden Theatre
New York City
212
83
1,672
Lunt-Fontanne Theatre
New York City
222
82
1,532
Winter Garden Theatre
New York City
226
80
1,456
Majestic Theatre
New York City
220
91
1,234
Lunt-Fontanne Theatre
New York City
225
81
1,583
August Wilson Theatre
New York City
228
78
1,234
Majestic Theatre
New York City
250
81
1,456
1-10 of 202 rows
First
Previous
1
2
3
4
....
21
Next
Last
Column Actions
Ask AI
Sort Ascending
Sort Desceding
Filter Column
Add Column
Aggregates
Average
Count Distinct
List Values
Explore and transform data
Leverage both chat and point and click for Al, to do last mile transformations.
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Includes
100 LLM calls
Al-powered code editor
10 threads
1 data source
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Free
Includes
100 LLM calls
Al-powered code editor
10 threads
1 data source
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/user/month
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500 Fast LLM calls/ month
3 data sources
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See how we compare against others in performance, growth
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faster than ever
Unlock endless possibilities with Tura
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