Amazon S3 JSON File Connector for MS Access In this article you will learn how to integrate Amazon S3 JSON File data in MS Access without coding in just a few clicks (live / bi-directional connection to Amazon S3 JSON File). Amazon S3 JSON File Connector can be used to read JSON Files stored in AWS S3 Buckets. Using this you can easily integrate AWS S3 JSON File data. It's supports latest security standards, and optimized for large data files. It also supports reading compressed files (e.g. GZip /Zip).. Using Amazon S3 JSON File Connector you will be able to connect, read, and write data from within MS Access. Follow the steps below to see how we would accomplish that. Download Documentation The driver mentioned above is part of ODBC PowerPack which is a collection of high-performance Drivers for various API data source (i.e. REST API, JSON, XML, CSV, Amazon S3 and many more). Using familiar SQL query language you can make live connections and read/write data from API sources or JSON / XML / CSV Files inside SQL Server (T-SQL) or your favorite Reporting (i.e. Power BI, Tableau, Qlik, SSRS, MicroStrategy, Excel, MS Access), ETL Tools (i.e. Informatica, Talend, Pentaho, SSIS). You can also call our drivers from programming languages such as JAVA, C#, Python, PowerShell etc. If you are new to ODBC and ZappySys ODBC PowerPack then check the following links to get started. ODBC PowerPack - System Requirements and Installation Getting Started - Using ODBC PowerPack ODBC API Driver Help File

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Create ODBC Data Source (DSN) based on ZappySys Amazon S3 JSON Driver

Step-by-step instructions

To get data from Amazon S3 JSON File using MS Access we first need to create a DSN (Data Source) which will access data from Amazon S3 JSON File. We will later be able to read data using MS Access. Perform these steps:

1. Install ZappySys ODBC PowerPack.

2. Open ODBC Data Sources (x64):
   

3. Create a User Data Source (User DSN) based on ZappySys Amazon S3 JSON Driver

   ZappySys Amazon S3 JSON Driver

   
   You should create a System DSN (instead of a User DSN) if the client application is launched under a Windows System Account, e.g. as a Windows Service. If the client application is 32-bit (x86) running with a System DSN, use ODBC Data Sources (32-bit) instead of the 64-bit version.

4. Create and configure a connection for the Amazon S3 storage account.

   

5. You can use select your desired single file by clicking [...] path button.

   mybucket/dbo.tblNames.json

   dbo.tblNames.json

   
   
   
   ----------OR----------

   You can also read the multiple files stored in Amazon S3 Storage using wildcard pattern supported e.g. dbo.tblNames*.json.
   

   Note: If you want to operation with multiple files then use wild card pattern as below 
   (when you use wild card pattern in source path then system will treat target path as folder regardless you end with slash)
   
   mybucket/dbo.tblNames.json (will read only single .JSON file)
   mybucket/dbo.tbl*.json (all files starting with file name)
   mybucket/*.json (all files with .json Extension and located under folder subfolder)
   

   mybucket/dbo.tblNames*.json

   
   
   
   ----------OR----------

   You can also read the zip and gzip compressed files also without extracting it in using Amazon S3 JSON Source File Task.

   mybucket/dbo.tblNames*.gz

   

6. Now select/enter Path expression in Path textbox to extract only specific part of JSON string as below ($.value[*] will get content of value attribute from JSON document. Value attribute is array of JSON documents so we have to use [*] to indicate we want all records of that array)
   

   NOTE: Here, We are using our desired filter, but you need to select your desired filter based on your requirement.
   

7. Navigate to the Preview Tab and let's explore the different modes available to access the data.
   

   1. --- Using Direct Query ---

      Click on Preview Tab, Select Table from Tables Dropdown and select [value] and click Preview.
      

   2. --- Using Stored Procedure ---

      Note : For this you have to Save ODBC Driver configuration and then again reopen to configure same driver. For more information click here.
      

      Click on the Custom Objects Tab, Click on Add button and select Add Procedure and Enter an appropriate name and Click on OK button to create.
      

      1. --- Without Parameters ---

         Now Stored Procedure can be created with or without parameters (see example below). If you use parameters then Set default value otherwise it may fail to compilation)
         
         

      2. --- With Parameters ---

         Note : Here you can use Placeholder with Paramters in Stored Procedure.
         Example : SELECT * FROM $ WHERE OrderID = '<@OrderID, FUN_TRIM>' or CustId = '<@CustId>' and Total >= '<@Total>'
         

         

   3. --- Using Virtual Table ---

      Note : For this you have to Save ODBC Driver configuration and then again reopen to configure same driver. For more information click here.
      

      ZappySys APi Drivers support flexible Query language so you can override Default Properties you configured on Data Source such as URL, Body. This way you don't have to create multiple Data Sources if you like to read data from multiple EndPoints. However not every application support supplying custom SQL to driver so you can only select Table from list returned from driver.

      Many applications like MS Access, Informatica Designer wont give you option to specify custom SQL when you import Objects. In such case Virtual Table is very useful. You can create many Virtual Tables on the same Data Source (e.g. If you have 50 Buckets with slight variations you can create virtual tables with just URL as Parameter setting).

      vt__Customers
      DataPath=mybucket_1/customers.json
      
      vt__Orders
      DataPath=mybucket_2/orders.json
      
      vt__Products
      DataPath=mybucket_3/products.json
      

      1. Click on the Custom Objects Tab, Click on Add button and select Add Table and Enter an appropriate name and Click on OK button to create.
         
      2. Once you see Query Builder Window on screen Configure it.
         
      3. Click on Preview Tab, Select Virtual Table(prefix with vt__) from Tables Dropdown or write SQL query with Virtual Table name and click Preview.
         

8. Click OK to finish creating the data source

9. That's it; we are done. In a few clicks we configured the to Read the Amazon S3 JSON File data using ZappySys Amazon S3 JSON File Connector

Read data in Microsoft Access from the ODBC data source

1. First of all, open MS Access and create a new MS Access database.

2. In the next step, start loading ODBC data source we created:

3. Then click next until data source selection window appears. Select the data source we created in one of the previous steps and hit OK:

   AmazonS3JsonFileDSN

   

4. Continue with tables and views selection. You can extract multiple tables or views:
   

5. Finally, wait while data is being loaded and once done you should see a similar view:

Using Linked Table for Live Data (Slow)

Linked tables in Microsoft Access are crucial for online databases because they enable real-time access to centralized data, support scalability, facilitate collaboration, enhance data security, ease maintenance tasks, and allow integration with external systems. They provide a flexible and efficient way to work with data stored in online databases, promoting cross-platform compatibility and reducing the need for data duplication.

1. Real-Time Data Access:
   Access can interact directly with live data in online databases, ensuring that users always work with the most up-to-date information.
2. Centralized Data Management:
   Online databases serve as a centralized repository, enabling efficient management of data from various locations.
3. Ease of Maintenance:
   Updates or modifications to the online database structure are automatically reflected in Access, streamlining maintenance tasks.
4. Adaptability to Changing Requirements:
   Linked tables provide flexibility, allowing easy adaptation to changing data storage needs or migration to different online database systems.

Let's create the linked table.

1. Launch Microsoft Access and open the database where you want to create the linked table.

2. Go to the "External Data" tab on the Ribbon. >> "New Data Source" >> "From Other Sources" >> "ODBC Database"

3. Select the option "Link to Data Source by creating a linked table:

4. Continue by clicking 'Next' until the Data Source Selection window appears. Navigate to the Machine Data Source tab and select the desired data source established in one of the earlier steps. Click 'OK' to confirm your selection.

   AmazonS3JsonFileDSN

   

5. Proceed to the selection of Tables and Views. You have the option to extract multiple tables or views:
   

6. When prompted to select Unique Key column DO NOT select any column(s) and just click OK:

7. Finally, Simply double-click the newly created Linked Table to load the data:

Guide to Effectively Addressing Known Issues

Discover effective strategies to address known issues efficiently in this guide. Get solutions and practical tips to streamline troubleshooting and enhance system performance, ensuring a smoother user experience.

Fewer Rows Imported

The reason for this is that MS Access has a default query timeout of 60 seconds, which means it stops fetching data if the query takes longer than that. As a result, only a limited number of rows are fetched within this time frame.

To address this, we can adjust the Query Timeout by following the steps below.

The path may vary depending on the MS Access bitness, such as 32-bit versus 64-bit.

\HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Jet\4.0\Engines\ODBC

\HKEY_LOCAL_MACHINE\SOFTWARE\WOW6432Node\Microsoft\Jet\4.0\Engines\ODBC

\HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Office\ClickToRun\REGISTRY\MACHINE\Software\Microsoft\Office\16.0\Access Connectivity Engine\Engines\ODBC

We can identify this issue by examining the Fiddler Log, as MS Access doesn't display any error regarding partial import, which is quite unusual

Please refer to this link : How to use Fiddler to analyze HTTP web requests

#Deleted word appears for column value in MS Access for Linked Table mode

If you used Linked Table mode to get external data and it shows #deleted word rather than actual value for column after you open then most likely its following issue.

Make sure to re-create Linked Table and DO NOT select any key column when prompted (Just click OK)
How to Fix

Table Selection UI Opening Delays

The Table selection UI takes a significant amount of time to open after clicking the 'New Data Source' -> 'Other Data Sources' -> 'ODBC'

The reason for this issue is that MS Access sends a dummy query, leading to several unnecessary pagination cycles before an error is thrown. To mitigate this, we can prevent wasted cycles by configuring the 'Throw error if no match' setting on the Filter Options Tab.

Enhancing Performance through Metadata Addition (Reduces Query Time)

We can optimize query performance by creating Virtual Tables (i.e. views with custom SQL) on Datasource and incorporating META=static columns. Learn how to capture static metadata in this guide.
Performance Options - Generate Metadata Manually

Execute the query initially, save the metadata by selecting 'Save to Meta' (choose Compact Format), and then click 'Save to Clipboard.' Utilize the resulting list by pasting it into the META attribute as follows: 'META=paste here.'

SELECT * FROM products
    WITH(
        META='id:String(20); title:String(100);  description:String(500);'
    )

Optimize Workflow with Automated Import

Employ Automated Import when Linked Tables are not feasible, and we need to depend on Imported Tables with static data.

While using Linked Tables sometime it encounter errors, and we are left with no alternative but to utilize Imported Tables, Automatic Refresh becomes crucial in such scenarios.

Here's a guide on automating refreshes. We can set up automatic refresh on different events, such as when the database opens, a form is opened, or a button is clicked.

To initiate the import process, follow these steps:

• Perform the data import using the standard manual steps.
• In the final step, we'll encounter a checkbox labeled 'Save Import Steps.' Ensure to check this option.
• After saving the steps, we can locate their name in the Save Imports UI. Identify the name associated with the saved steps.
• "Now, we can execute the code as shown below:"

Private Sub cmdYes_Click()
    Label0.Visible = True
    DoCmd.RunSavedImportExport "Import-DATA.products"
    Label0.Visible = False
End Sub

Advanced topics

Create Custom Stored Procedure in ZappySys Driver

You can create procedures to encapsulate custom logic and then only pass handful parameters rather than long SQL to execute your API call.

Steps to create Custom Stored Procedure in ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here

1. Go to Custom Objects Tab and Click on Add button and Select Add Procedure:
   

2. Enter the desired Procedure name and click on OK:
   

3. Select the created Stored Procedure and write the your desired stored procedure and Save it and it will create the custom stored procedure in the ZappySys Driver:
   Here is an example stored procedure for ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here
   

   CREATE PROCEDURE [usp_get_orders]
       @fromdate = '<<yyyy-MM-dd,FUN_TODAY>>'
    AS
       SELECT * FROM Orders where OrderDate >= '<@fromdate>';
   

   
   

4. That's it now go to Preview Tab and Execute your Stored Procedure using Exec Command. In this example it will extract the orders from the date 1996-01-01:
   

   Exec usp_get_orders '1996-01-01';

   
   

5. Let's generate the SQL Server Query Code to make the API call using stored procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([MY_API_SERVICE], 'EXEC usp_get_orders @fromdate=''1996-07-30''')

   
   

6. Now go to SQL served and execute that query and it will make the API call using stored procedure and provide you the response.
   

Create Custom Virtual Table in ZappySys Driver

ZappySys API Drivers support flexible Query language so you can override Default Properties you configured on Data Source such as URL, Body. This way you don't have to create multiple Data Sources if you like to read data from multiple EndPoints. However not every application support supplying custom SQL to driver so you can only select Table from list returned from driver.

If you're dealing with Microsoft Access and need to import data from an SQL query, it's important to note that Access doesn't allow direct import of SQL queries. Instead, you can create custom objects (Virtual Tables) to handle the import process.

Many applications like MS Access, Informatica Designer wont give you option to specify custom SQL when you import Objects. In such case Virtual Table is very useful. You can create many Virtual Tables on the same Data Source (e.g. If you have 50 URLs with slight variations you can create virtual tables with just URL as Parameter setting.

1. Go to Custom Objects Tab and Click on Add button and Select Add Table:
   

2. Enter the desired Table name and click on OK:
   

3. And it will open the New Query Window Click on Cancel to close that window and go to Custom Objects Tab.

4. Select the created table, Select Text Type AS SQL and write the your desired SQL Query and Save it and it will create the custom table in the ZappySys Driver:
   Here is an example SQL query for ZappySys Driver. You can insert Placeholders also. Read more about placeholders here
   

   SELECT
     "ShipCountry",
     "OrderID",
     "CustomerID",
     "EmployeeID",
     "OrderDate",
     "RequiredDate",
     "ShippedDate",
     "ShipVia",
     "Freight",
     "ShipName",
     "ShipAddress",
     "ShipCity",
     "ShipRegion",
     "ShipPostalCode"
   FROM "Orders"
   Where "ShipCountry"='USA'

   
   

5. That's it now go to Preview Tab and Execute your custom virtual table query. In this example it will extract the orders for the USA Shipping Country only:
   

   SELECT * FROM "vt__usa_orders_only"

   
   

6. Let's generate the SQL Server Query Code to make the API call using stored procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([MY_API_SERVICE], 'EXEC [usp_get_orders] ''1996-01-01''')

   
   

7. Now go to SQL served and execute that query and it will make the API call using stored procedure and provide you the response.
   

Conclusion

In this article we discussed how to connect to Amazon S3 JSON File in MS Access and integrate data without any coding. Click here to Download Amazon S3 JSON File Connector for MS Access and try yourself see how easy it is. If you still have any question(s) then ask here or simply click on live chat icon below and ask our expert (see bottom-right corner of this page).

Download Amazon S3 JSON File Connector for MS Access Documentation 

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