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(Un)Perplexed Spready v1.2.X — SQL Query in spreadsheets

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(Un)Perplexed Spready with SQL Query

SQL Query in (Un)Perplexed Spready — Your Spreadsheet Is Now a Database

Introduction

(Un)Perplexed Spready is a spreadsheet application that combines the power of traditional spreadsheets with advanced artificial intelligence capabilities. Version 1.2.X represents the biggest leap in the application's history, bringing a range of features that elevate data work to an entirely new level.

This version introduces four major improvement areas: Web Search, Vision & Document Processing, SQL Query, and Advanced Statistics.
Best of all, SQL Query and Advanced Statistics functions are completely free! If you are looking for a free statistical software, you are on the right page!

Spreadsheet applications are excellent for smaller datasets and ad-hoc analyses. But when you need to join data from multiple sheets, filter by complex criteria, or calculate aggregates — traditional formulas become complicated and hard to maintain.

(Un)Perplexed Spready v1.2.X introduces SQL Query functionality — every sheet in your workbook becomes a SQL table, and you can write standard SQL queries for data analysis.

Best of all: SQL Query is FREE — forever!

Workbook-as-Database Architecture

(Un)Perplexed Spready treats your entire workbook as a database:

  • Each sheet = One SQL table
  • Sheet name = Table name
  • First row = Column headers (field names)
  • Subsequent rows = Data records

Example:

Sheet "Sales":

Product Quantity Price Date
Widget A 100 25.00 2026-01-15
Widget B 50 40.00 2026-01-16

SQL query:

SELECT Product, SUM(Quantity) as Total
FROM Sales
GROUP BY Product
ORDER BY Total DESC

How to Use

Opening the SQL Query Window

  1. Open (Un)Perplexed Spready
  2. Load or create a workbook with data
  3. Click Tools → SQL Query from the menu

SQL Query Window Contains:

  • SQL Editor (top) — Write and edit SQL queries
  • Results Grid (bottom) — Display results
  • Toolbar — Quick access to functions

Toolbar Functions:

  • Execute (F5) — Run SQL query
  • Clear — Clear editor
  • Export to Sheet — Export results to new sheet
  • Save Query — Save SQL to file (.sql)
  • Load Query — Load SQL from file
  • Query Builder — Visual query builder
  • COMMIT - used for saving update query result back into source spreadsheet

Supported SQL Commands

SELECT — Retrieving Data

-- Basic SELECT
SELECT * FROM Sales

-- Selected columns
SELECT Product, Quantity, Price FROM Sales

-- Filtering
SELECT * FROM Sales WHERE Quantity > 100

-- Sorting
SELECT * FROM Sales ORDER BY Date DESC

-- Limit
SELECT * FROM Sales LIMIT 10

JOIN — Joining Tables

-- Join two sheets
SELECT p.Product, p.Quantity, c.Category
FROM Sales p
JOIN Catalog c ON p.Product = c.Product

-- LEFT JOIN
SELECT p.Product, p.Quantity, c.Category
FROM Sales p
LEFT JOIN Catalog c ON p.Product = c.Product

Aggregations

-- COUNT
SELECT COUNT(*) as Row_Count FROM Sales

-- SUM
SELECT Product, SUM(Quantity) as Total
FROM Sales
GROUP BY Product

-- AVG
SELECT AVG(Price) as Average_Price FROM Sales

-- MIN / MAX
SELECT MIN(Date) as From_Date, MAX(Date) as To_Date FROM Sales

-- GROUP BY with HAVING
SELECT Product, SUM(Quantity) as Total
FROM Sales
GROUP BY Product
HAVING SUM(Quantity) > 100

INSERT, UPDATE, DELETE

-- INSERT
INSERT INTO Sales (Product, Quantity, Price, Date)
VALUES ('Widget D', 75, 30.00, '2026-01-18')

-- UPDATE
UPDATE Sales SET Price = 28.00 WHERE Product = 'Widget A'

-- DELETE
DELETE FROM Sales WHERE Quantity < 50

Important: Changes are executed in memory. To save them permanently, use COMMIT or export results to a new sheet.

Writing Changes to Sheets

All changes are executed in memory, not directly on sheets. For permanent saving:

Option 1: COMMIT

COMMIT

Saves all modified tables back to the workbook.

NOTE: JanSQL was originally designed to work with csv files inside a folder. In order to actually commit changes inside (Un)Perplexed Spready spreadsheet, you need to additionally click "COMMIT" button in GUI. So, two-step commit is reuiqred: commit statement inside SQL commits change to a dataset in memory, while commit button commits it back into underlying spreadsheet file. To persist changes, you also need to save the spreadsheet.

Option 2: SAVE TABLE

SAVE TABLE Results AS New_Sheet

Saves query result as a new sheet.

Option 3: Export to Sheet

Click the Export to Sheet button in the toolbar. Results are saved to a new sheet.

Real-World Examples

Sales Analysis

-- Monthly sales by product
SELECT
   Product,
   strftime('%Y-%m', Date) as Month,
   SUM(Quantity) as Total_Quantity,
   SUM(Quantity * Price) as Total_Revenue
FROM Sales
GROUP BY Product, strftime('%Y-%m', Date)
ORDER BY Month, Total_Revenue DESC

Inventory with Catalog

-- Current inventory with product info
SELECT
   i.Product,
   c.Category,
   c.Supplier,
   i.Quantity,
   i.Quantity * c.Cost_Price as Value
FROM Inventory i
JOIN Catalog c ON i.Product = c.Product
WHERE i.Quantity > 0
ORDER BY Value DESC

Customer 360

-- Complete customer overview
SELECT
   c.Name,
   c.Surname,
   COUNT(o.ID) as Order_Count,
   SUM(o.Total) as Total_Spent,
   MAX(o.Date) as Last_Order
FROM Customers c
LEFT JOIN Orders o ON c.ID = o.Customer_ID
GROUP BY c.ID
ORDER BY Total_Spent DESC

QC Analysis

-- Defects by line and cause
SELECT
   Line,
   Cause,
   COUNT(*) as Defect_Count,
   ROUND(COUNT(*) * 100.0 / (SELECT COUNT(*) FROM Defects), 2) as Percentage
FROM Defects
WHERE Date >= '2026-01-01'
GROUP BY Line, Cause
ORDER BY Defect_Count DESC

SQL Editor Features

Syntax Highlighting

SQL keywords are colored for easier reading:

  • SELECT, FROM, WHERE — blue
  • AND, OR, NOT — orange
  • COUNT, SUM, AVG — green
  • Strings — red

Auto-Complete

Press Ctrl+Space for:

  • SQL keywords
  • Table names (sheets)
  • Column names

Helper Lists

  • Tables list — All available sheets
  • Fields list — Columns of selected table
  • Operators list — SQL operators

Working with Dates

janSQL does not use strong data types — everything is string. For working with dates, use ISO 8601 format:

  • Date: YYYY-MM-DD (e.g., 2026-03-04)
  • Date and time: YYYY-MM-DDThh:mm:ss (e.g., 2026-03-04T14:30:00)

-- Filter by date
SELECT * FROM Sales WHERE Date >= '2026-01-01'

-- Date range
SELECT * FROM Sales
WHERE Date BETWEEN '2026-01-01' AND '2026-01-31'

-- Extract month
SELECT strftime('%Y-%m', Date) as Month FROM Sales

Credits

SQL Query functionality is based on the proven janSQL engine (by Jan Verhoeven, http://jansfreeware.com), the same engine used in ZMSQL package and MightyQuery software.

Thanks to Jan Verhoeven for contributing to the open-source community!

Technical Details

Performance

  • In-memory processing — Everything runs in memory for speed
  • Semi-compiled expressions — Optimized expression evaluation
  • No server required — No need to install a database

Limitations

  • Single-user — One user at a time
  • No transactions — No ACID transactions
  • Limited JOIN types — Basic JOIN types supported

Supported File Formats

  • .xlsx — Microsoft Excel
  • .ods — LibreOffice/OpenOffice
  • .csv — Comma-separated values

Download SQL Query Manual

You can download corresponding manuals here: 

https://matasoft.hr/SQL_User_Manual.pdf

https://matasoft.hr/janSql-hlp.pdf

Conclusion

SQL Query in (Un)Perplexed Spready brings the power of SQL directly to your spreadsheet. No server, no configuration, no additional costs.

Whether you need to join data from multiple sheets, filter by complex criteria, or calculate aggregates — SQL does it elegantly and efficiently.

SQL Query in (Un)Perplexed Spready is and will always be FREE!

© 2026 Matasoft.

Further Reading

(Un)Perplexed Spready v1.2.X — A New Chapter in AI-Powered Spreadsheets

Introduction to (Un)Perplexed Spready

Download (Un)Perplexed Spready

Purchase License for (Un)Perplexed Spready

Various Articles about (Un)Perplexed Spready

AI-driven Spreadsheet Processing Services