ElasticSearch Connector for Power BI In this article you will learn how to integrate ElasticSearch data in Power BI without coding in just a few clicks (live / bi-directional connection to ElasticSearch). Read / write ElasticSearch data inside your app; perform many ElasticSearch operations without coding, just use easy to use high performance API Connector for ElasticSearch. Using ElasticSearch Connector you will be able to connect, read, and write data from within Power BI. 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

Connect to ElasticSearch in other apps Connect to ElasticSearch in SSIS Connect to ElasticSearch in SQL Server Connect to ElasticSearch in SSRS Connect to ElasticSearch in Informatica Connect to ElasticSearch in MS Access Connect to ElasticSearch in MS Excel Connect to ElasticSearch in SSAS Connect to ElasticSearch in C# Connect to ElasticSearch in Python Connect to ElasticSearch in JAVA Connect to ElasticSearch in Tableau Connect to ElasticSearch in SAP Crystal Reports Connect to ElasticSearch in Azure Data Factory (Pipeline) Connect to ElasticSearch in Azure Data Factory (SSIS) Connect to ElasticSearch in Talend Studio Connect to ElasticSearch in UiPath Connect to ElasticSearch in PowerShell Connect to ElasticSearch in ODBC

Video Tutorial - Integrate ElasticSearch data in Power BI

This video covers following and more so watch carefully. After watching this video follow the steps described in this article.

• How to download / install required driver for ElasticSearch integration in Power BI
• How to configure connection for ElasticSearch
• Features about API Driver (Authentication / Query Language / Examples / Driver UI)
• Using ElasticSearch Connection in Power BI

Create ODBC Data Source (DSN) based on ZappySys API Driver

Step-by-step instructions

To get data from ElasticSearch using Power BI we first need to create a DSN (Data Source) which will access data from ElasticSearch. We will later be able to read data using Power BI. 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 API Driver

   ZappySys API 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. When the Configuration window appears give your data source a name if you haven't done that already, then select "ElasticSearch" from the list of Popular Connectors. If "ElasticSearch" is not present in the list, then click "Search Online" and download it. Then set the path to the location where you downloaded it. Finally, click Continue >> to proceed with configuring the DSN:

   ElasticSearchDSN

   ElasticSearch

   

5. Now it's time to configure the Connection Manager. Select Authentication Type, e.g. Token Authentication. Then select API Base URL (in most cases, the default one is the right one). More info is available in the Authentication section.

    Basic Authentication (UserId/Password) [Http]

   Fill in all required parameters and set optional parameters if needed:

   ElasticSearchDSN

   ElasticSearch

   Basic Authentication (UserId/Password) [Http]

   http://localhost:9200

   Required Parameters
   Optional Parameters
   UserName	Fill in the parameter...
   Password	Fill in the parameter...
   IgnoreSSLCertificateErrors	Fill in the parameter...

   

    Windows Authentication (No Password) [Http]

   Fill in all required parameters and set optional parameters if needed:

   ElasticSearchDSN

   ElasticSearch

   Windows Authentication (No Password) [Http]

   http://localhost:9200

   Required Parameters
   Optional Parameters
   IgnoreSSLCertificateErrors	Fill in the parameter...

   

6. Once the data source has been configured, you can preview data. Select the Preview tab and use settings similar to the following to preview data:
   

7. Click OK to finish creating the data source.

Video instructions

Read ElasticSearch data in Power BI using ODBC

1. Once you open Power BI Desktop click Get Data to get data from ODBC:
   

2. A window opens, and then search for "odbc" to get data from ODBC data source:
   

3. Another window opens and asks to select a Data Source we already created. Choose ElasticSearchDSN and continue:

   ElasticSearchDSN

   

4. Most likely, you will be asked to authenticate to a newly created DSN. Just select Windows authentication option together with Use my current credentials option:

   ElasticSearchDSN

   

5. Finally, you will be asked to select a table or view to get data from. Select one and load the data!
   

6. Finally, finally, use extracted data from ElasticSearch in a Power BI report:
   

Import ElasticSearch data into Power BI from SQL Query

If you wish to import ElasticSearch data from SQL query rather than selecting table name then you can use advanced options during import steps (as below). After selecting DSN you can click on advanced options to see SQL Query editor.

Import ElasticSearch data into Power BI using SQL Query (ODBC Data source)

Edit Query / Using Parameters in Power BI (Dynamic Query)

let
    vKey=paraAPIKey,
    Source = Odbc.Query(
    "dsn=ZS-OData Customers", 
    "SELECT * FROM value WITH (SRC='http://httpbin.org/post'," 
    & "METHOD='POST'," 
    & "HEADER='Content-Type:application/json'," 
    & "BODY=@'{""CallerId"":1111, ""ApiKey"":""" & vKey & """}')")
in
Source

Edit Query Settings after Import

There will be a time you need to change initial Query after dataset import in Power BI. Not to worry, just follow these steps to edit your SQL.

Edit Power BI Data Source SQL after REST / SOAP Web Service Import

Working with Gateways in Power BI (Schedule Import)

1. In the last section, we Published the report. Power BI may ask you to SIGN IN.
   

   Sign in Power BI

2. Select the Workspace and select Datasets
   

   Go to workspace and dataset

3. Right-click the report and select Settings.
   

   Specify settings for the report

4. The system will ask for a Gateway. Stay here.
   

   Add Power BI Gateway

5. Use the following link to install a Data Gateway:

   https://docs.microsoft.com/en-us/power-bi/service-gateway-onprem

6. Run the installer and press Next
   

   Gateway installer

7. Select the option On-premises data gateway (recommended). This option allows access to multiple users and can be used by more applications than Power BI.
   

   Choose Power BI option

8. The installer will show a warning message.
   

   Warning message during installation

9. Select the path to install and check the I accept the terms.
   

   Accept terms

10. Specify the email address to use the gateway.
    

    Register email address

11. After entering the email, write the gateway name and a recovery key. Make sure to confirm the recovery key.
    

    Enter recovery key

Manage gateways and configure the schedule

1. The next step is to go to manage gateway
   

   Power BI - Manage Gateway Setting

2. In order to get the connection string, we will need the connection string of the ZappySys API Driver. In the first section of this post, we explained how to configure it. Press Copy Connection String
   

   Connection properties

3. Once that the data is copied, add a New data Source. In Data Source Name, enter the Data Source Name of the ZappySys API Driver in step 13 and in Data Source Type, select ODBC. In connection string copy and paste from the clipboard of the step 13 and press Add.
   

   ZappySys connection properties in Power BI

4. Once added the gateway. You can see the schedule refresh to On and Add another time to add the time where you want to refresh the data.
   

   Schedule gateway

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.
   

Actions supported by ElasticSearch Connector

ElasticSearch Connector Examples for Power BI Connection

This page offers a collection of SQL examples designed for seamless integration with the ZappySys API ODBC Driver under ODBC Data Source (36/64) or ZappySys Data Gateway, enhancing your ability to connect and interact with Prebuilt Connectors effectively.

SELECT * FROM create_index WITH(Name='my_new_index_name', ContineOnErrorForStatusCode=1)

SELECT * FROM delete_index WITH(Name='my_index_name', ContineOn404Error=1 )

SELECT * FROM generic_request 
WITH(Url='/my_index_name'
	, RequestMethod='PUT'
--	, Body='{}'
--	, Headers='X-Hdr1:aaa || x-HDR2: bbb'
	, Meta='acknowledged:bool'
	)

SELECT * FROM Indexes

SELECT * FROM get_index_metadata WITH (Index='my_index_name')

SELECT * FROM MyIndexOrAliasName --WITH(Query='{"match": { "PartNumber" : "P50" } }')

SELECT * FROM MyIndexOrAliasName --WITH(Query='{"match": { "PartNumber" : "P50" } }')

SELECT * FROM MyIndexOrAliasName WITH(Query='{"match": { "comment" : "TV" } }')
		
		--or use below - slight faster (avoids table / alias list validation)
		--SELECT * FROM search WITH(Index='MyIndexName', Query='{"match": { "comment" : "TV" } }')
		--SELECT * FROM search WITH(Index='MyIndexName', Alias='MyAliasName', Query='{"match": { "comment" : "TV" } }')

SELECT * FROM MyAliasName WITH(Query='{"match": { "comment" : "TV" } }')
		
		--or use search endpoint then you must supply both Index name and Alias name 
		--calling /search endpoint in FROM clause is slight faster (avoids table / alias list validation)
		--SELECT * FROM search WITH(Index='MyIndexName',Index='MyAliasName', Query='{"match": { "comment" : "TV" } }')

SELECT * FROM count WITH(Index='MyIndexOrAliasName') --//get count of documents in index / alias named MyIndexOrAliasName
SELECT * FROM count WITH(Index='*') --//get count of documents in all indices (total distinct _id found across all indices + alias) 
SELECT * FROM count WITH(Index='MyIndex1,MyIndex2,MyAlias1,MyAlias2')--//get count of documents in indices named MyIndex1, MyIndex2 and Alias named MyAlias1,MyAlias2
SELECT * FROM count WITH(Index='MyIndexOrAliasName', Query='{"match": { "comment" : "TV" } }') --//get count of documents in MyIndex where comment field contains word "TV"

SELECT * FROM count WITH(Index='MyIndexOrAliasName') --//get count of documents in index / alias named MyIndexOrAliasName
SELECT * FROM count WITH(Index='*') --//get count of documents in all indices (total distinct _id found across all indices + alias)
SELECT * FROM count WITH(Index='MyIndexOrAlias1,MyIndexOrAlias2') --//get count of documents in MyIndex1 and MyIndex2
SELECT * FROM count WITH(Index='MyIndex', Query='{"match": { "comment" : "TV" } }') --//get count of documents in Index named MyIndex where comment field contains word "TV"
SELECT * FROM count WITH(Index='MyAlias', Query='{"match": { "comment" : "TV" } }') --//get count of documents in Alias named MyAlias where comment field contains word "TV"

SELECT _id
        , JSON_ARRAY_FIRST(colors) as first_color
        , JSON_ARRAY_LAST(colors) as last_color
        , JSON_ARRAY_NTH(colors,3) as third_color
        , JSON_VALUE(locationList,'$.locationList[0].country') as first_preferred_country
        , JSON_VALUE(locationList,'$.locationList[?(@country=='India')].capital as capital_of_india
FROM shop WHERE _Id='1'

INSERT INTO MyIndex([MyCol1], [MyCol2] ) VALUES (100, 'A1')

INSERT INTO MyIndex(_id, [MyCol1], [MyCol2] ) VALUES ('A1234', 100, 'A1')

INSERT INTO MyIndexName ([Location.City], [Location.ZipCode], [raw::ColorsArray], [raw::SomeNestedDoc] )
VALUES ('A1234', 'Atlanta', '30060', '["red","green","blue"]', '{"Col1":"aaa","Col2":"bbb","Col3":"ccc"}' )

INSERT INTO shop(_RAWDOC_) 
VALUES(@'{"create":{"_index":"shop","_id":"1"}}\n{"name":"record-1","colors":["yellow","orange"]}\n{"create":{"_index":"shop","_id":"2"}}\n{"name":"record-2","colors":["red","blue"]}\n')

UPDATE MyIndex
  SET Col1 = 'NewValue-1', Col2 = 'NewValue-2'
  WHERE _Id = 'A1234'

UPDATE shop SET _rawdoc_ = @'{"update": {"_index": "shop", "_id": "1"}}\n{ "doc": {"colors":["yellow","orange"] } }\n{"update": {"_index": "shop", "_id": "2"}}\n{ "doc": {"colors":["yellow","blue"] } }\n'

UPDATE MyIndex
  SET name = 'abcd', [raw::colors]='["yellow","red"]', [raw::location]='{x:10, y:20}' 
  WHERE _id='1'

DELETE MyIndex WHERE _id = 'A1234'

Conclusion

In this article we discussed how to connect to ElasticSearch in Power BI and integrate data without any coding. Click here to Download ElasticSearch Connector for Power BI 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 ElasticSearch Connector for Power BI Documentation 

More integrations

Other application integration scenarios for ElasticSearch

SSIS

SQL Server

SSRS

Informatica

MS Access

MS Excel

SSAS

C#

Python

JAVA

Tableau

SAP Crystal Reports

Azure Data Factory (Pipeline)

Azure Data Factory (SSIS)

Talend Studio

UiPath

PowerShell

ODBC

Other connectors for Power BI

Amazon Ads

Amazon MWS

Amazon Selling Partner (SP-API)

Asana

Azure DevOps

Cosmos DB

DropBox

ElasticSearch

FastSpring

Google BigQuery

Google Calendar

Google Drive

Google Sheets

Hubspot

Jira

Mailchimp

ManagedEngine ServiceDesk Plus (Zoho)

Nativo

OData

OneDrive

Outlook Mail (Office 365)

Power BI

ServiceNow

SharePoint Online

Shopify

Smartsheet

Stripe

YouTube

Zendesk

Zoho CRM

Zoho SalesIQ

Zoom

REST API

JSON

JSON File

XML

SOAP

XML File

JDBC-ODBC Bridge

Salesforce

CSV

Amazon S3 JSON File

Amazon S3 XML File

Amazon S3 CSV File

Azure Blob JSON File

Azure Blob XML File

Azure Blob CSV File

FTP/SFTP JSON File

FTP/SFTP XML File

FTP/SFTP CSV File

Build your own Custom API Connector

Download ElasticSearch Connector for Power BI Documentation

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