Direct connection

To connect a new data source, select Data Sources from the top navigation and click + New Data Source. Select your data source type from the list. Fill out the connection form, and click Connect.

Aside from providing connection details, some data sources require a schema name to reflect properly. If you’re unsure of what schema you should use, you can run the following query to find out which schema to reflect after you’ve connected the data source.

Most direct connections are straightforward, but some require a few extra connection steps. Data sources that require special instructions are listed below.

Click the blue +Add a Datasource button

Data Sources
Amazon Athena Amazon Aurora Amazon RDS Amazon Redshift
Amazon VPC CSV Uploads DashDB SSL DB2 SSL
Google Analytics Google BigQuery Google Cloud SQL Google Sheets
Heroku Maria DB MongoDB MySQL
Oracle PostgreSQL Presto Rackspace Cloud
Segment Snowflake Spark SQL SQL Server (Azure)
SQL Server Stitch Vertica VoltDB

Amazon Athena

To connect to an Amazon Athena data source, you will need the following information:

Amazon Athena source user permissions

Data Sources

To grant Chartio the proper read permissions required to connect to an Athena data source, you will need to create a new user and new policy in IAM.

  1. Create a new user that has programmatic access to Chartio
  2. Assign this user the ‘AWSQuicksightAthenaAccess’ policy (this gives the user access to Athena).
  3. Create a new policy in IAM to allow the Chartio user access to the specific buckets that contain your data. You will need to give List->HeadBucket, List->ListBucket, and Read-GetObject for the specific buckets and all objects in the buckets.
  4. Assign this new policy to the Chartio user you created.

The IAM user that created the API access keys will need to have S3 access to both the S3 bucket where the data is read from and the S3 bucket where the query results are stored. The AWSQuicksightAthenaAccess policy only gives access to the query result S3 bucket. You will also need to add a policy to the user so it has access to the data.

Chartio does not have a direct connection to Amazon S3, as Chartio supports primarily relational SQL databases. Amazon Athena has the capability of accessing your data stored in an S3 bucket. For more information about this process please refer to the Amazon Athena documentation.

Amazon Aurora

If your instance is in a VPC (for example, Aurora Serverless), see our VPC instructions.

Follow the RDS Instructions to add Chartio to your RDS Security Groups. This will allow our server to connect to your RDS instance.

Next, retrieve read-only credentials for authentication, and complete the connection form for Amazon Aurora.

Amazon RDS


You will use your Amazon RDS endpoint and port number from the Instances section of your RDS Dashboard in the Host and Port fields when connecting your data source.

RDS dashboard provides needed details

RDS Security Groups

In order for Chartio to connect to your database, your RDS security group needs to be modified in order to white-label Chartio’s inbound IP address. To view your security groups, access your RDS Dashboard.

Click on the VPC security group assigned to your to DB from the console and this will bring you to the security group page where you can add a new inbound rule. A form for a CIDR will be presented. Please add the following IP address to your Security Group:

RDS Security Groups settings

Connecting your data source

Adding Chartio’s external IP to your Security Group will allow our server to connect to your RDS instance. However, you will still need to provide read-only credentials for authentication. Please follow the individual instructions for your database platform.

See how to connect Amazon RDS to Chartio:

Amazon Redshift

Redshift Security Groups

For Chartio to connect to your database, you’ll need to whitelist our inbound IP address ( ) in your Cluster’s Security Group settings.

If your database server, RDS instance or Redshift cluster is on a private subnet of an Amazon VPC, follow our VPC connection instructions instead.

Log in to the Redshift Management Console and select Clusters from the left sidebar. Select the cluster you want to connect to Chartio.

The Cluster Details page will display. In the Cluster Security Groups section, click the Security Group you want to add Chartio to.

In the Security Group, click the Inbound Rules tab at the bottom of the page, then click the Edit button. Set the Type to Redshift, and adjust the Port if needed. Enter the following into the Source field:

Connection Details

You can find the information needed to connect on the Clusters page of the Amazon Redshift Management Console. Locate the Endpoint, Port, Database Name, and Master Username.

Redshift expiring SSL certificate

On our side, we do not check the validity (signing) of their SSL certificate, just that you have one for encryption purposes. This shouldn’t affect the Chartio connection. If you find you do run into issues with the connection, please let us know and we can investigate further.

Amazon VPC

If your database server, RDS instance or Redshift cluster is on a private subnet of an Amazon VPC, follow our instructions example.

CSV Uploads

A comma-separated values (CSV) file stores tabular data in plain text where each line of the file is a data record separated by commas. CSV files can be easily uploaded to Chartio and queried and visualized like any other data source. Uploading multiple CSVs together allows you to use each as a table within the same database. CSVs uploaded to Chartio will be queried in PostgreSQL syntax.

Preparing your CSV for Upload

  • File uploads are limited to 100MB each. Larger files can be separated into multiple files and appended.
  • If your data is currently in Excel, please see converting Excel workbooks to CSV files.
  • Remove extra headers and footers. Your CSV should be in raw table format, with all data arranged in columns and one header row as seen below.
  • Header row should contain no special characters, only numbers, letters, or underscores.

Example Table

DateCityTemperature in Celsius
9/20/2017San Francisco19
9/21/2017San Francisco18

When opened in a text editor, the file should be in this format:

Date, City, Temperature in Celsius 9/20/2017, San Francisco, 19 9/21/2017, Austin, 34 9/21/2017, San Francisco, 18 9/21/2017, Austin, 33

Uploading and Processing Your Files

In the top navigation menu, select Data Sources. At the top of your data sources list, click + Add Data Source. From the Databases list, choose CSV Upload.

Select one or more (up to 100) CSV files and select Open. Each file will become a separate table in the CSV data source. Click Upload when ready.

If you’d like, edit the Table Name field. Uncheck First row has column headers if applicable, and manually enter header names. Review the data types Chartio has auto-detected for each column, and change if necessary.

Upload CSV files

Chartio tries to guess the date format of your columns, but it isn’t always correct. Verify that the date format is correct, and edit if necessary. See our formatting reference table below.

Format the date for the csv

Click Upload when ready.

View the Schema Editor to rename the data source, change the names of individual tables and columns, and create foreign keys between tables.

Adding CSV Data to an Existing CSV Data Source

You can update the data in an existing CSV in the following ways:

  • Replace an existing CSV table
  • Append to an existing CSV table
  • Add a new CSV table

From your data source settings, click Upload Alternate CSV files, located in the General tab.

Upload alternate CSV files form the General tab

Choose from the list what you would like to do with the new data: Append or Replace existing data, or create a new table in the CSV data source.

If you choose Append or Replace, a dropdown will appear. Select the table from the dropdown you would like to update.

Select from the dropdown

The file uploader will appear. Drag your file into the window, manually select the file, or paste in the data using the Manual input option.

Uncheck First row has column headers if applicable, and confirm the encoding setting is correct.

If you’ve chosen Append or Replace, you’ll see an interface that will allow you to choose how new columns map to existing columns. Chartio will convert data types to match an existing column’s data type whenever possible.

When you’re satisfied with the settings and mappings (if applicable), click Upload New Data.

Click Upload New Data when you have set the desired preferences

Date Formatting Reference

 TokenExample output
 M1..12 or 01..12
ISO WeekW1..53
Day of MonthD1..31 or 01..31
Day of YearDDD1..365 or 001..365
Hour (24)H1..24 or 01..24
Hour (12)h1..12 or 01..12
AM / PMAAM, PM or am, pm
Minutem1..59 or 01..59
Seconds1..59 or 01..59
Sub-secondS1 or 01 or 001
TimezoneZZ-07:00, -06:00 ... +06:00, +07:00
 Z-0700, -0600 ... +0600, +0700
Unix TimestampX1381685817


  • Dates can include special characters above by using brackets. For example, Y2015-W01 has format [Y]YYYY-[W]WW
  • For 6-digit milliseconds, use SSS[000]

See how to connect a CSV file to Chartio:


Configure SSL support on your database, then check the Connect using SSL checkbox in the Chartio connection form.

See our basic connection instructions.


Configure SSL support on your database, then check the Connect using SSL checkbox in the Chartio connection form.

See our basic connection instructions.

Google Analytics

If you’re already signed into the Google account you want to associate Chartio with, you’ll be prompted with a simple permissions request to allow access. If you’re not, you’ll need to sign in to your Google account before access is allowed.

If you plan to use Google Analytics custom segments, make sure the login you use for Chartio to connect to the database has permissions to access those segments.

Click Accept when prompted by Google to give Chartio permission to access your Google Analytics data

Once you’ve granted permission, you’ll be directed back into the Chartio interface. You can now create charts with your Google Analytics data.

Aggregating Google Analytics data

The Google Analytics API only allows querying directly for measures and dimensions and does not allow Chartio to perform aggregations on the data.

Many Google Analytics metrics are already aggregated. For example, Sessions is a count of sessions and Visitors is a count of visitors.

If you would like to apply aggregations on top of Google Analytics metrics, such as average of Sessions, you can do so in the Data Pipeline.

For definitions of individuals metrics, see Google’s Dimensions & Metrics Explorer.

Can’t find a metric?

Chartio hides some lesser-used metrics by default to make your data easier to navigate. If you can’t find a column, please see our instructions for unhiding metrics in your schema.

Analytics 360 (Premium) Accounts

If you have an Analytics 360 (premium) GA Account, please contact to enable additional custom variables and dimensions.

Google BigQuery

To connect your BigQuery account to Chartio, you’ll need to set up a Service Account and upload the generated key to Chartio.

Create a Service Account

Log in to Google Cloud Platform and navigate to the project you want to use in Chartio.

In the sidebar, select IAM & admin and choose Service accounts.

From the Google Cloud Platform, click Service accounts

Click Create Service Account.

Click Create Service Account

Enter a name—you may want to name it Chartio so you can remember its purpose later—and under Role check BigQuery Data Viewer and BigQuery User in the BigQuery menu option. Ensure both roles are selected; if either is missing, Chartio will be unable to connect to your BigQuery data.1

Name it and select BigQuery Viewer and BigQuery User

Click the Create button

Check the Furnish a new private key checkbox, and ensure JSON is selected under Key type. Click Create.

Save the JSON file to your computer.

  1. It is possible to use only the BigQuery User role but that service account would need to be added to each dataset individually.

Upload key to Chartio

In Chartio, select Data Sources > + Add Data Source > Google BigQuery, and upload the JSON file you downloaded in the previous step. Note: it can take a few minutes for Google to accept the JSON key. If you get an error uploading the JSON file to Chartio, wait a few minutes and try again.

Access Multiple Projects

To access additional BigQuery projects with a single Service Account, you’ll need to add the client ID to the additional projects from the Google Cloud Platform console.

From Google Cloud Platform, select IAM from the sidebar. Find the service account, and copy the member name.

Set the permissions

Switch to another project you want to connect to Chartio, and click Add at the top of the page. In the Members field, paste the member name you copied earlier. Under Role, select BigQuery User and BigQuery Data Viewer.

Click Add and paste the copied member name

Once this is finished, you can use the same JSON file you downloaded earlier to connect your second BigQuery project to Chartio.

See how to connect BigQuery to Chartio:

Google Sheets via BigQuery

If you’ve added Google Sheets tables to your BigQuery project, you can query them in Chartio from your BigQuery connection after a few settings updates. Your BigQuery account must use a service account connection to enable this feature.

Enable Google Drive API in the project

Log in to your Google Cloud Console. Select your project from the top dropdown. From the left navigation, choose APIs & Services, then choose Dashboard. At the top of the page, click Enable APIs and Services. Use the search bar to search for Google Drive API, select it, and click Enable.

Add service account email to the Google Sheet

From your Google Cloud Console, select IAM & admin from the left sidebar, then select Service accounts. Copy the value in the Service account email column. If you don’t have a service account yet, follow the instructions above for connecting a BigQuery account.

Open your Google Sheet, and click on the Share button. Click Advanced at the bottom, and in the Invite people text input, enter the Service account email value you copied earlier.

Google Cloud SQL

In Chartio’s connection form, copy Chartio’s IP address, which is located under the Hostname or IP field.

Connect a data source

Open a new browser window and go to your Project list in the Google Developers Console. Select your Project from the list. Choose Cloud SQL from the left navigation, then select your Google Cloud SQL instance. Click the Access Control tab.

Open the Google Developers console

Click Add new under the Authorized Networks section of your Access Control settings, and add Chartio’s IP address that you copied earlier.

You’ll see your Google Cloud SQL IP address on this tab as well, which you’ll need to enter into the Chartio connection form.

Google Cloud SQL SSL Connection

Network Connectivity Issues

Ensure that the Chartio IP address has been whitelisted to access the Google Cloud SQL instance. To do this, in the Google Cloud console:

  1. Navigate to the SQL server instance
  2. View the Connections tab
  3. Ensure the Public option is selected and click Add Network
  4. Enter Chartio as the name of the network with the following CIDR

Securing SSL Connections in Google Cloud

Google Cloud SQL generates a custom certificate authority to generate per-client certificates. However, Chartio doesn’t support configuring client certificates at this time. In order to connect to Google Cloud SQL, you must allow insecure SSL connections.

This will disable Google Cloud SQL from only allowing connections from known client certificates but if configured properly in Chartio, it will still establish an SSL connection.

Using PostgreSQL

Chartio’s Google Cloud SQL connector only supports MySQL at this time. However, you can still connect to PostgreSQL Google Cloud SQL instances using a normal PostgreSQL data source in Chartio.

Google Sheets

Chartio’s Google Sheets connection allows you to automatically import Google Sheets to your account and use them like you would any other data source: a spreadsheet corresponds to a database and worksheets correspond to tables. Any updates made to rows in your Sheets data will be immediately queryable in Chartio.

Preparing your Google Sheet

Formatting requirements:

  • Remove extra headers and footers.
  • Each worksheet should be in a tabular format, starting in the top-left cell, with all data arranged in columns and one header row with no empty header cells.
  • The header row should contain no special characters (including newlines). Headers should contain only numbers, letters, and/or underscores.
  • Use the Google Sheets Format menu to correctly specify the format of a column.
  • Note: If your Google Sheet uses a comma for the decimal separator, data may not be accurately being brought in Chartio. The issue is that Chartio expects the decimal separator to be a dot. By opening your Google Sheet and changing the locale of your spreadsheet (File > Spreadsheet settings) to, for example, United States, it will change the decimal separator to a dot. This will allow Chartio to detect the column as the correct percentage value.

Connecting a Google Sheet

If you’re already signed into the Google account you want to associate Chartio with, you’ll be prompted with a simple permissions request to allow access. If you’re not, you’ll need to sign in to your Google account before access is allowed.

Google Sheets Limitations

Renaming the spreadsheet, a worksheet, or a column is currently not supported. This will be treated as a deletion and addition and will cause errors with any charts currently using a renamed object. Moving a column or worksheet is supported.

The user that initially added the data source will need to remain as authorized and maintain access to the spreadsheet. If you’d like to change the authorizing user or re-authorize, this can be done from the Connection tab within the specific Google Sheet’s settings.

Any column named “Id” will be renamed to “Id1”. This is due to Google Sheets returning the row ID as “Id” which will show as a hidden column in your schema.

Google Sheets SQL Mode syntax

  • Strings must be wrapped in single quotes (e.g., ‘John Doe’).
  • Use Oracle’s syntax for date formatting using the FORMAT() function.

See how to upload your Google Sheets as a new data source and start building chart with it in Chartio:


To connect a Heroku instance to Chartio, you’ll need to retrieve the connection URL from your Heroku account.

Log in to the Heroku Postgres interface. You should see a list of your Apps. Click on the App that corresponds to your database—it will likely have the same name as your database.

Click on the Settings tab, then click ‘Reveal config vars’. Copy the value for DATABASE_URL, and paste it into a text editor. The URL will be in the following format:


Copy the individual values (username, password, hostname, etc.) from the DATABASE_URL and paste them into the connection form in Chartio.

Click Reveal Config Vars

Config Variables


Heroku wisely enables PostgreSQL SSL connections by default. Every data connection Chartio makes is encrypted this way.


Chartio supports connections to MariaDB, however by default MariaDB may use an out dated authentication method not supported by JDBC connections. You will need to update the user’s password to the new version before connecting with Chartio. Please see the documentation regarding old passwords here and setting a new password here.

If your instance is in a VPC, see our VPC instructions.

If your database is on Amazon RDS, add Chartio to your RDS Security Groups. This will allow our server to connect to your RDS instance.

Otherwise, see our basic connection instructions.


Chartio supports MongoDB through a tool developed by Stripe called MoSQL. MoSQL creates and live-updates a PostgreSQL instance of your MongoDB data. As an added bonus, you’ll be creating a backup copy of your data, which is something we always recommend.

We have several customers, including MongoHQ, who are successfully using MoSQL to import their MongoDB databases to Chartio.

The basic steps are:

  1. Create PostgreSQL database
  2. Follow Stripe’s instructions for syncing your MongoDB data to your PostgreSQL instance
  3. Connect PostgreSQL data source to Chartio

MoSQL does not support MongoDB 3.2 or later. If you are using a newer version of MongoDB, other options include:

  • Stitch or other ETL tools
  • Momy, a tool to replicate MongoDB to MySQL in realtime
  • rollback to MoSQL-supported version of MongoDB


If your database is on Amazon RDS, please visit the RDS setup documentation to first enable Chartio in your security groups before following these steps.

MySQL read-only user

Chartio requires a read-only user for connecting to your database. Here is a sample GRANT statement for creating a read-only user:

ON $database_name.*
TO $user@`` IDENTIFIED BY '$password';

Where $database_name, $user, and $password are described in the Chartio connection form. Copy this command and paste it into a MySQL shell to create the user. This will grant the user read-only access to ALL tables in your database. If you would like to restrict access to only certain tables in your database, please see Chartio’s help center.

MySQL SSL Connection

Instructions on creating a certificate and SSL connection can be found in the MySQL SSL connection documentation.

See a step-by-step video below showing how to connect your MySQL database to Chartio:


See our basic connection instructions.


If your PostgreSQL database is hosted on Heroku or Amazon RDS, please follow those instructions for connecting your instance.

PostgreSQL read-only user

The Chartio connection form requires a read-only username and password, which you’ll need to create on your PostgreSQL database before you submit the connection form.

See a step-by-step video below showing you how to connect your PostgreSQL database to Chartio:

Allowing Chartio to connect to your database

By default, PostgreSQL restricts connections to hosts and networks included in the pg_hba.conf file. You may need to add Chartio’s IP address to this file to allow connectivity to your database.

To allow the user ‘chartio_read_only’ to connect to the database ‘mydatabase’ from Chartio’s IP address you would add the following lines to pg_hba.conf:

host mydatabase chartio_read_only md5

You may need to restart your PostgreSQL server for the changes to take effect.

For more details on modifying the pg_hba.conf file consult the PostgreSQL documentation.


A Presto connection can be made using either a direct connection or a reverse SSH tunnel connection.

To set up an SSH tunnel connection, please see our Tunnel Connection instructions. One the tunnel is set up, add a new Presto data source in Chartio via Data Sources > + Add Data Source.

Form requirements for both connection types:

  • Hostname or IP (Direct Connection only)
  • Database Port (Direct Connection only)
  • Database Username (Direct Connection only)
  • Catalog
    You can find a list of catalogs in the etc/catalog directory of your Presto installation. Catalogs will each have their own file with the extension .properties.
  • Schema Name
    In the etc/catalog directory, find your Catalog. Open its .properties file to locate schema information.
  • SSH public key (Tunnel Connection only) Your public key is required to authorize Chartio to connect to your Presto database. Locate it on your Presto server and paste it into the Chartio connection form.

For more information, please see the Presto Documentation.

Rackspace Cloud

If your Rackspace instance is located on an ORD Rackspace server, Chartio can connect using your private IP address. Simply enter your private IP address into the MySQL connection form in Chartio.

If your Rackspace instance is located in a region other than ORD, you’ll need to set up a Cloud Load Balancer, which will provide you with a public IP address. You can use this public IP address in the MySQL connection form to connect your Rackspace instance to Chartio.

Information about setting up a Cloud Load Balancer is available in Rackspace’s documentation.


Click the green Add Warehouse + button

Enable Segment warehouse support

To use Chartio with Segment data, you will first need to enable Segment to pipe your data into your warehouse.

Enable Segment in your Connection Settings

Log in to Segment and navigate to the Warehouse tab. If you do not have a warehouse enabled, choose the “Add Warehouse” button and enter your warehouse credentials in the setup flow. Otherwise, choose the warehouse you want to connect with Chartio and click the tile to “View Details”.

Obtain Segment connection details

Once in the options menu for your chosen warehouse, navigate to Settings > Connection and copy those credentials.

Connect Segment to Chartio

In Chartio, add your Segment data source as an Amazon Redshift connection. Paste the values from the Segment connection settings into the input boxes in the Chartio connection form and click Connect.



  • Snowflake warehouse must be set to AUTO-SUSPEND

Obtain Snowflake connection details

All connection details are case-sensitive. Snowflake stores object names in uppercase unless you quote (“”) the names when you create the objects. This includes Warehouse Name, Database Name, and Schema Name.

  • Account name
    The first part of your Snowflake URL:
  • Account user
    The username you use to log in to your Snowflake console.
  • Warehouse name
    Click “Warehouses” from within your Snowflake console to view a list of warehouses. Any warehouse in your account will work with any database.
  • Region
    If not US West Region, your region will be listed in your Snowflake console URL:
  • Database
    Click “Databases” from within your Snowflake console to view a list of databases.
  • Database password
    The password you use with your Account user to log in to your Snowflake console.
  • Schema name
    Click “Databases” from within your Snowflake console, then click the name of the database you would like to use. Switch to the “Schemas” tab to view a list of schemas for that database. Chartio will automatically default the schema to public in the connection form unless a schema name is entered.

Connect Snowflake to Chartio

In Chartio, select Data Sources from the top menu, choose + Add Data Source, then select Snowflake. Enter the connection details obtained in the previous step into the connection form and click Connect.

Note: Your schema name is case sensitive.

Time Zones

Chartio sets Snowflake data sources to UTC. It is not currently possible to override this time zone setting.

Suspended warehouse

Chartio will automatically resume a suspended warehouse prior to schema refresh. Chartio will NOT resume a suspended warehouse to run a query.

Spark SQL

A Spark SQL connection can be made using a direct connection.

From the top navigation, select Data Sources. Click the + Add Data Source button, and choose Spark SQL from the list.

You’ll see the following form:


Enter your connection details and click Connect. Once the connection is established, Chartio will retrieve your schema and the data source will be ready for use.

For more information, please see

SQL Server (Azure)

Before connecting SQL Server to Chartio, log in to your Windows Azure account, select SQL Databases from the navigation, then select the name of the database you would like to connect to.

Make note of the server name and port number at the bottom of the page. This is the information you will use in the Host and Port fields when creating a connection to Chartio. Select the Dashboard link at the top of the page.

Click the Dashboard link on chinook

Scroll down and select the link to Manage allowed IP addresses in the bottom right-hand corner of the screen.

Click Manage allowed IP addresses

Add a new rule using the following IP address:

Rule Name: Chartio
Start IP Address:
End IP Address:

Click the Save button at the bottom of the page.

Once you have collected your information from your Windows Azure management console and added access to Chartio’s external IPs, you can follow the instructions to connect SQL Server to Chartio.

MySQL Azure connection

We currently do not have have listed support for MySQL Azure, only SQL Server Azure.

We can only have a connection that does not require an SSL CA file. You will need to find a way to ‘Allow Unsecured Connections’. We will still connect with an SSL connection from our end, but cannot use their certificates.

SQL Server

Chartio supports connecting to your SQL Server instance via a direct connection from our server to yours. For SQL Server instances hosted on Windows Azure or Amazon RDS, please refer to the instructions linked.

Currently, Chartio supports SQL authentication only. Chartio requires a read-only user for connecting to your database. To create this user please follow our instructions for granting table level permission in SQL Server.

Chartio officially supports Microsoft SQL Server 2008 R2, 2012, 2014, and 2016. Earlier versions of SQL Server may be compatible but are not tested, and support is not guaranteed.

Before you complete the connection form in Chartio, you will need to create a read-only user that Chartio can use to connect.

Select your SQL Server version from the drop-down menu and enter the necessary information in the corresponding fields. When finished, click Connect.

Connecting SQL Server from a local machine

There are a couple configurations you will need to make to use Chartio with a local SQL Server.

  1. Forward traffic from our external IP,, on port 1433 to the internal IP address of your desktop computer.
  2. Allow access to SQL Server via the Windows firewall. Refer to this page for more information about configuring the Windows firewall.

If you have an IT person or a network administrator, they will know how to do this for you.

See a step-by-step video below showing you how to connect your SQL Server database to Chartio:

Connecting to SQL Server 2008 R2 using SSL

SQL Server 2008 R2 versions prior to 10.50.2811.0 have a bug which causes encrypted JDBC connections to fail. This issue has been resolved in SQL Server 2008 R2 Service Pack 1, Cumulative Update 6 (See KB 2653857).

If the SQL Server instance does not force all connections to be encrypted (and you are okay with not encrypting the connection), you can uncheck the Connect using SSL box.

If the SQL Server 2008 R2 instance is setup to force encryption, or you do not want to turn off SSL, the only option is to upgrade to Service Pack 1, Cumulative Update 6 or greater.

How to find your version of SQL Server

Open Microsoft SQL Server Management Studio and select Help > About.

How to find if the server instance is set to force encryption:

Open Sql Server Configuration Manager > expand SQL Server Network Configuration and right click on Protocols for MSSQLSERVER > select Properties > select Flags tab.

If the value of ForceEncryption is set to Yes, all connections must be encrypted, otherwise, the server will reject the connection.


Stitch uses Amazon Redshift for data warehousing. To connect Stitch to Chartio, you’ll need to do the following:

  • Whitelist Chartio’s IP address in Redshift
  • Enter the Redshift connection details into Chartio

Whitelisting Chartio’s IP Address

See our Redshift instructions for whitelisting Chartio’s IP address.

Add Stitch to Chartio

The following instructions can be used to set up a Direct Connection to your Stitch Redshift data warehouse. If you plan on using an SSH Tunnel to connect, see our Tunnel connection instructions.

Connection details can be found in your AWS management console, as described in the previous step.

Open the AWS console

In your Chartio account, select Data Sources > + Add Data Source. Select Amazon Redshift, then fill in the following:

  • Hostname or IP: Your endpoint, excluding the colon and port number.
  • Database Port
  • Connect using SSL: Leave checked to use SSL.
  • Database Username: The user you want to use to connect to Chartio; could be the master user, the Stitch user, or something else.
  • Database Password: Password associated with the database user.
  • Database Name: The name of the database that you used to connect to Stitch. This should be the same database that’s listed in the Database field in your Stitch Warehouse Settings.
  • Extract Schema: Leave checked.
  • Time Zone Support: Select Time Zone to automatically apply your organization’s and dashboards’ time zone to your data.
  • Data Source Alias: A nickname for your database.

When finished, click Connect.


From the top navigation, select Data Sources. Click the +Add Data Source button, and choose Vertica from the list.

You’ll see the following form:

Vertical Data Source form

Enter your connection details and click Connect. Once the connection is established, Chartio will retrieve your schema and the data source will be ready for use.


Follow our basic connection instructions.

Querying VoltDB

VoltDB will terminate long-running queries. As such, Chartio recommends that you query materialized views only, and hide standard tables in your Chartio schema.

To determine which tables are which, navigate to your-database-IP-address:8080 in your browser, switch to the Schema tab, and select Schema from the subnavigation. Tables and Materialized Views are labeled in the schema.

VoltDB console