Relational databases

A detailed overview of the DbSource and DbDestination connector.


The DbSource give you access to any database table or with your database. Or you can directly pass an sql statement that is used as source. The use of the DbSource is very straight forward. You simple pass a connection manager (the right one for your database) and a table name.

Let’s assume that SouceTable has two columns and is defined like this:

CREATE TABLE SourceTable (
    Value VARCHAR(50) NULL

Now we can create our strongly typed object (POCO) to match with this definition:

Let’s assume we create a POCO (Plain old component object) MySimpleRow that looks like this:

public class MyRow {
    public int Id { get; set;}
    public string Value { get; set;}

Now we can setup our data flow like this:

SqlConnectionManager connMan = new SqlConnectionManager("Data Source=.;Integrated Security=SSPI;Initial Catalog=ETLBox;");
DbSource<MyRow> source = new DbSource<MyRow>(connMan, "SourceTable");

ETLBox will automatically extract missing meta information during runtime from the source table and the involved types. In our example, the source table has columns with exact same name as the object - ETLBox will check this and write data from the Id column into the Id property, and data from the column Value into the Value property. Each record in the source will be a new object that is created and then passed to the connected components.

In case you want to test yourdata flow, you could connect your database source to a memory destination and check the data that you retrieved:

MemoryDestination dest = new MemoryDestination();
Console.WriteLine("Loaded "+dest.Data+" rows!");

Working with Sql statements

For the DbSource, you can also specify some Sql code to retrieve your data:

DbSource<MyRow> source = new DbSource<MyRow>() {
    ConnectionManager = connMan, 
    Sql = "SELECT Id, Value FROM SourceTable"

There is an implict column mapping that happens when you Sql statements. In this example, the Sql statement would create a result set with the columns Id and Value. This does match with the property names in your POCO that we defined previously. If you sql statement would produce different column names, then you can either use define a column mapping or you use the AS keyword to rename your columns. (SELECT Col1 AS Id, Col2 AS Value FROM SourceTable)

Using dynamic object

The default implementation of DbSource will use an ExpandoObject. This dynamic object will then properties with the same names as the columns in your source.

DbSource source = new DbSource(connMan, "SourceTable");

No object is needed when using this. Make sure that all other components also either use the default implementation, or alternatively you cast the ExpandoObject into an object or array of your choice. This can be done e.g. with a RowTransformation

Using string arrays

Also you can use the DbSource to read your data directly into an array. This could be a string array. The order of the columns of your table or you sql code is then equals the order in your array. Also, you don’t need any other object definition then.

DbSource<string[]> source = new DbSource<string[]>(connMan, "SourceTable");


The DbDestination will write that data from your flow into the a table. Like the DbSource, you need to pass a connection manager and the destination table name. For any property in your object, the data will be written into the table if the column names match with the property name.

public class MyRow
    public int Id { get; set; }
    public string Value { get; set; }
SqlConnectionManager connMan = 
    new SqlConnectionManager("Data Source=.;Integrated Security=SSPI;");
DbDestination<MyRow> dest = new DbDestination<MyRow>(connMan, "DestinationTable");

If your table has the columns Id and/or Value, the data of your flow will be written into this columns.

Using dynamic objects

Of course you can also use the default implementation of the DbDestination to write data into a table.

SqlConnectionManager connMan = 
    new SqlConnectionManager("Data Source=.;Integrated Security=SSPI;");
DbDestination dest = new DbDestination(connMan, "DestinationTable");

Like with an object, the properties of the ExpandoObject are used to map the values to the right columns. Only if the ExpandoObject object has a property with the same name as the column in the destination table, data is written into this column. Unfortunately, the Column mapping attributes are not working here.

Using arrays

You can also use the DbDestination with array.

SqlConnectionManager connMan = 
    new SqlConnectionManager("Data Source=.;Integrated Security=SSPI;");
DbDestination<string[]> dest = new DbDestination<string[]>(connMan, "DestinationTable");

The data is written into the columns in the same order as they are stored in the array. E.g., if your string array has three values, these values are stored into the first, second and third column of your destination table. If your destination table has more columns, these will be ignored. Identity columns (or auto increment / serial values) are ignored.

Batch Size

By default, the DbDestination will create batches of data that then are inserted in whole into the database. This is faster than creating a single insert for each incoming row. So the DbDestination is a little bit different from the other destinations: It will always wait until it has received the full amount of rows needed for a batch, and then do the insert. The default batch size is 1000. You can play around with the batch size to gain higher performance. 1000 rows per batch is a solid value for most operations. If you encounter the issue that inserted the data into the destinations takes to long, try to reduce the batch size significantly.

var dest = new DbDestination<MyRow>(connMan, "DestinationTable");
dest.BatchSize = 10000;

BatchSize in Odbc & OleDb

If you leave the default value for batch size set, it will be changed to 100 rows for Odbc and OleDb connections. As the connection here is much slower than “native” connections, and bulk inserts need to be translated into “INSERT INTO” statements, 100 rows per batch leads to a much better performance than 1000 rows.

Column Mapping

Of course the property names in the object and the column names can differ - ETLBox will only load columns from a source where it can find a matching property with the same name. If the data type is different, ETLBox will try to automatically convert the data. If the names are different, you can use the attribute ColumnMap to define the matching columns name for a property.

Let’s reconsider our example at the beginning. We create a table like this:

CREATE TABLE SourceTable (
    Value VARCHAR(50) NULL

Now we could define our POCO using the ColumnMap attribute. In this example, we replace the property Id with the property Key. In order to still be able to read data from the Id column, we add the ColumnMap attribute above it. Please note that the data type was changed to string as well - ETLBox will automatically try to convert the integer values into a string if data types are not matching.

public class MyRow {
    public string Number { get; set;}
    public string Value { get; set;}

The setup of our data flow would be left untouched:

SqlConnectionManager connMan = 
    new SqlConnectionManager("Data Source=.;Integrated Security=SSPI;");
DbSource<MyRow> source = new DbSource<MyRow>(connMan, "SourceTable");

Column Mapping with ExpandoObject

If you use the default implementation of DbSource/DbDestination, then the ExpanoObject will be used internally. This dynamic object doesn’t allow you to set attributes as decorators for property. Instead you can pass the attributes manually to the ColumnMapping property.

var source = new DbSource(connectionManager, "TableName");
source.ColumnMapping = new[]
    new ColumnMap() { DbColumnName = "Id", PropertyName = "Number"},
    new ColumnMap() { DbColumnName = "Col2", PropertyName = "Text"}

Column Converters

Both DbSource and DbDestination allows the use of column converters. These are special converter function that are executed for every record in a particular column. The idea of this converters is to do special data conversion directly in the soruce/destination which are not supported by ETLBox. E.g. for SqlServer, it is quite common to use a date format like “20200101”. This date format is not supported by the C# DateTime object, so you need to define your own column conversion function if you want to write this date format directly from a string value into a DbDestination.

Here is an example how to write the string value “20200101” into a database column “DateCol”.

  CREATE TABLE TestTable (

public class MyRow
    public string DateCol { get; set; } = "20200101";

DbDestination<MyRow> dest = new DbDestination<MyRow>(conn, "TestTable");

dest.ColumnConverters = new[] {    
    new ColumnConverter("DateCol", dateCol => {
        if (dateCol == null) 
            return new DateTime(1990, 1, 1);
            return DateTime.ParseExact((string)dateCol, 
                    "yyyyMMdd", CultureInfo.InvariantCulture);

Table Definitions

If you pass a table name to a DBsource or DbDestination or a Sql statement to a DbSource, the meta data of the table is automatically derived from that table or sql statement by ETLBox. For table or views this is done via a Sql statement that queries system information, and for the Sql statement this is done via parsing the statement. If you don’t want ETLBox to read this information, or if you want to provide your own meta information, you can pass a TableDefinition instead.

This could look like this:

var TableDefinition = new TableDefinition("tableName"
    , new List<TableColumn>() {
    new TableColumn("Id", "BIGINT", allowNulls:false, 
                     isPrimaryKey: true, isIdentity:true)),
    new TableColumn("OtherCol", "NVARCHAR(100)", allowNulls: true)

var DbSource<type> = new DbSource<type>() {  
  SourceTableDefinition = TableDefinition

ETLBox will use this meta data instead to get the right column names.