Fastest Way to Populate an Excel File in IronXL

Curtis Chau
Curtis Chau
Updated: October 29, 2026

When you build large spreadsheets in IronXL, the data-loading method you pick has a big effect on how long generation takes. The benchmark below compares three common approaches against the same 20,000-row by 55-column dataset.

Benchmark

Every test populates identical data and writes the result to disk as an .xlsx file. Both duration (in seconds) and the resulting file size were recorded.

  • Adding data cell by cell: ~13 sec, 3094 KB
  • Loading from DataTable: ~3.4 sec, 3094 KB
  • Loading from CSV: ~4.1 sec, 3094 KB

All three produce the same file size. What changes dramatically is the time to generate it.

The Methods

Option 1: Adding Data Cell by Cell

This approach assigns a value to each individual cell through nested loops. It is the slowest of the three.

string[] fruits = { "Apples", "Apricot", "Banana", "Blackberry", "Blueberry", "Boysenberry", "Canary Melon", "Cantaloupe",
                        "Currants", "Dates (tree dried only) Dragon Fruit", "Durian (purchase cut) Figs", "Gooseberry", "Grapes", "Grapefruit",
                        "Lemon", "Lime", "Loganberry", "Longan", "Loquat", "Lychee", "Mandarin", "Mango",
                        "Blood Orange", "Papaya", "Passion Fruit", "Peach", "Pear", "Persimmon", "Pineapple", "Plum", "Honeydew",
                        "Rambutan", "Starfruit", "Tamarind", "Yuzu", "Açaí", "Abiu", "Ackee", "Breadfruit", "Cempedak",
                        "Cherimoya", "Buddha's Hand", "Citron", "Finger Lime", "Kumquat", "Pomelo", "Tangelo", "Ugli Fruit",
                        "Galia Melon", "Kiwano (Horned Melon)", "Mouse Melon", "Muskmelon",
                        "cherry", "nectarine", "Butternut squash"};
var workbook = WorkBook.Create(ExcelFileFormat.XLSX);
var worksheet = workbook.CreateWorkSheet("Fruits");
var columnsTitles = GetExcelCellLetters(fruits.Length);
for (int col = 0; col < columnsTitles.Count; col++)
{
    string columnLetter = columnsTitles[col]; // To avoid interpolation that can cause performance issues in large loops because it build string objects in every loop
    for (int row = 1; row <= 20000; row++)
    {
        worksheet[columnLetter + row].Value = fruits[col];
        //worksheet.Rows[row].Columns[columnLetter].Value.ToString();
    }
}
workbook.SaveAs("C:\\Temp\\ManualCell-by-CellAssignment.xlsx");
private static List<string> GetExcelCellLetters(int iMaxNum)
{
    string[] alphabet = { string.Empty, "A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U", "V", "W", "X", "Y", "Z" };
    IEnumerable<string> lst = (from c1 in alphabet
                               from c2 in alphabet
                               from c3 in alphabet.Skip(1)
                               where c1 == string.Empty || c2 != string.Empty
                               select c1 + c2 + c3).Take(iMaxNum);
    return lst.ToList();
}

Precomputing columnLetter outside the inner loop avoids string interpolation on every iteration, which otherwise allocates new strings millions of times over.

CellByCell

Option 2: Loading from a DataTable

Build a DataTable in memory, then hand it to IronXL in one call with LoadWorkSheet. This is one of the two fastest options, and from v2026.10.1 it is as fast as CSV or faster, and far quicker than manual cell insertion.

string[] fruits = { "Apples", "Apricot", "Banana", "Blackberry", "Blueberry", "Boysenberry", "Canary Melon", "Cantaloupe",
                        "Currants", "Dates (tree dried only) Dragon Fruit", "Durian (purchase cut) Figs", "Gooseberry", "Grapes", "Grapefruit",
                        "Lemon", "Lime", "Loganberry", "Longan", "Loquat", "Lychee", "Mandarin", "Mango",
                        "Blood Orange", "Papaya", "Passion Fruit", "Peach", "Pear", "Persimmon", "Pineapple", "Plum", "Honeydew",
                        "Rambutan", "Starfruit", "Tamarind", "Yuzu", "Açaí", "Abiu", "Ackee", "Breadfruit", "Cempedak",
                        "Cherimoya", "Buddha's Hand", "Citron", "Finger Lime", "Kumquat", "Pomelo", "Tangelo", "Ugli Fruit",
                        "Galia Melon", "Kiwano (Horned Melon)", "Mouse Melon", "Muskmelon",
                        "cherry", "nectarine", "Butternut squash"};
var workbook = WorkBook.Create(ExcelFileFormat.XLSX);
DataTable table = new DataTable("Fruits");
foreach (string fruitName in fruits)
{
    table.Columns.Add(fruitName);
}
int rowCount = 20000;
for (int i = 0; i < rowCount; i++)
{
    table.Rows.Add(fruits);
}
workbook.LoadWorkSheet(table);
workbook.SaveAs("C:\\Temp\\LoadDataTableDirectly.xlsx");

LoadWorkSheet(table) writes the entire table at once instead of touching cells individually, which is where the speedup comes from.

DataTable

Option 3: Loading from CSV

Write the data to a delimited .csv file, then read it back with LoadCSV. This is one of the two fastest options and the natural choice when your data is already flat and delimited.

string[] fruits = { "Apples", "Apricot", "Banana", "Blackberry", "Blueberry", "Boysenberry", "Canary Melon", "Cantaloupe",
                        "Currants", "Dates (tree dried only) Dragon Fruit", "Durian (purchase cut) Figs", "Gooseberry", "Grapes", "Grapefruit",
                        "Lemon", "Lime", "Loganberry", "Longan", "Loquat", "Lychee", "Mandarin", "Mango",
                        "Blood Orange", "Papaya", "Passion Fruit", "Peach", "Pear", "Persimmon", "Pineapple", "Plum", "Honeydew",
                        "Rambutan", "Starfruit", "Tamarind", "Yuzu", "Açaí", "Abiu", "Ackee", "Breadfruit", "Cempedak",
                        "Cherimoya", "Buddha's Hand", "Citron", "Finger Lime", "Kumquat", "Pomelo", "Tangelo", "Ugli Fruit",
                        "Galia Melon", "Kiwano (Horned Melon)", "Mouse Melon", "Muskmelon",
                        "cherry", "nectarine", "Butternut squash"};

            var sb = new StringBuilder();
            // Step 1: Add header row
            sb.AppendLine(string.Join(",", fruits));
            // Step 2: Add 20,000 identical rows
            string rowData = string.Join(",", fruits); // same as headers
            for (int i = 1; i < 20000; i++)
            {
                sb.AppendLine(rowData);
            }
            File.WriteAllText("C:\\Temp\\csvfile.csv", sb.ToString(), Encoding.UTF8);
            var workbook = WorkBook.LoadCSV("C:\\Temp\\csvfile.csv");
            workbook.SaveAs("C:\\Temp\\LoadFromCSV.xlsx");

LoadCSV parses the delimited file in bulk, so the cost is in writing and reading the intermediate .csv rather than per-cell assignment.

CSV

Which to Choose

  • For data already on disk: read it with CSV when the source is a flat, delimited file.
  • For data already in memory: load a DataTable; from v2026.10.1 it is the fastest or joint-fastest option.
  • For per-cell logic or styling: reach for cell-by-cell writing only then, since it is the slowest path.

Curtis Chau holds a Bachelor’s degree in Computer Science (Carleton University) and specializes in front-end development with expertise in Node.js, TypeScript, JavaScript, and React. Passionate about crafting intuitive and aesthetically pleasing user interfaces, Curtis enjoys working with modern frameworks and creating well-structured, visually appealing manuals.

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