When Stitch replicates your data, we’ll load it into the destination - or data warehouse - of your choosing. A data warehouse is a central repository of integrated data from disparate sources.

As we currently only allow you to connect one destination to your account, we recommend asking yourself the questions below before making your selection. By fully assessing each choice first, you’ll decrease the likelihood of needing to switch destinations or re-replicate all of your data at a later date.

  • Does it support all (or most of) your data sources?
  • Will the structure of the data replicated by Stitch work with how you plan to use it?
  • Do you need a fully-managed solution, or can you perform maintenance tasks on your own?
  • Does the provider’s pricing fall within your budget?

At the end of this article is a visual rollup of how each of Stitch’s destinations stack up against each other. This chart includes some supported limits (ex: length of table names), what task each destination excels at, and so on.

Getting Started, Fast

If you simply want to try Stitch or Redshift or if you don’t have the ability to spin up a Redshift cluster of your own in AWS, we recommend trying Panoply. With just a few clicks, you create your own fully-managed Redshift data warehouse and start replicating data in minutes.

Keep in mind that switching to a different destination at any point will require a full re-sync of your data.

Integration & Destination Compatibility

Some integrations may be partially or fully incompatible with some of the destinations offered by Stitch. For example: some destinations don’t support storing multiple data types in the same column. If a SaaS integration sends over a column with mixed data types, some destinations may “reject” the data.

For integrations that allow you to control how data is structured, you may be able to fix the problem at the source and successfully replicate the data. If this is not possible, however, Stitch may never be able to succesfully replicate the incompatible data.

Check Integration & Destination Compatibility

Data Structure

While the majority of your data will look the same across our destinations, there are some key differences you should be aware of.

Nested Data Structures

If you decide to use a destination that doesn’t natively support nested structures - meaning Redshift, Panoply, or PostgreSQL - Stitch will de-nest these structures. This means that Stitch will create subtables AND that your row count will be higher depending on the level of nesting.

Google BigQuery is currently the only destination that natively supports nested structures. This means nested records will be stored intact in a BigQuery data warehouse.

Check out the Handling of Nested Data & Row Count Impact for an in-depth look at what we mean by nested records, how Stitch handles nested data, and what those records will look like in your data warehouse.

BigQuery & Append-Only Replication

The current release of Stitch’s BigQuery destination uses Append-Only Incremental Replication.

For SaaS and database tables that use Incremental Replication, Stitch will replicate data into BigQuery in an append-only fashion. This means that data that updates existing an existing row will NOT overwrite the row. Instead, a new row with the new data will be appended to the end of the table.

This means that there can be many different rows in a BigQuery table with the same Primary Key, each representing what the data was at that moment in time. These are not duplicate rows - they’re “snapshots” of the record at different points.

For more info, check out this detailed explanation on Append-Only Replication or our recommendations for querying append-only tables.

Redshift vs. PostgreSQL

If you’ve worked with PostgreSQL in the past and are considering Redshift as your data warehouse, you should note that Redshift implements some Postgres features differently. In addition, some features, data types, and functions aren’t supported at all.

Setup & Maintenance

With the exception of a self-hosted PostgreSQL instance, all the destinations offered by Stitch are cloud-hosted databases, meaning you won’t have to factor in server maintenance when making a decision.

BigQuery, Panoply, and Heroku are fully-managed solutions that include routine maintenance and upgrades in their plans. In addition, these options require little to no technical knowledge to set up.

Redshift, Amazon Postgres-RDS, and self-hosted Postgres instances will require you to perform and schedule maintenance tasks on your own. Spinning up a Redshift and Amazon Postgres-RDS instance will require technical knowledge and familiarity with the Amazon Web Services (AWS) console.


Every destination offered by Stitch has its own pricing structure. Some providers charge by overall usage, others by an hourly rate or the amount of stored data. Depending on your needs, some pricing structures may fit better into your budget.

In the next section, you’ll find each destination’s pricing structure, including a link to detailed price info and whether a free option (trial or plan) is available. Here are a few things to keep in mind:

  • BigQuery: BigQuery’s pricing isn’t based on a fixed rate, meaning your bill can vary over time. To learn more about how Stitch may impact your BigQuery costs, click here.

  • Panoply: Panoply charges based on the amount of data stored and offers several plan options for your needs. Their free option includes up to 10 million stored rows per month, which is based on the daily average of the number of rows stored, not loaded.

  • PostgreSQL: The software for hosting your own PostgreSQL instance is open-source, meaning it’s free. Heroku and Amazon RDS have a variety of plans to choose from.

  • Redshift: Currently, Redshift bases their pricing on an hourly rate that varies depending on the type and number of nodes in a cluster. The type and number of nodes you choose when creating a cluster is dependent on your needs and data set, but you can scale up or down over time should your requirements change.

Comparing Destinations

BigQuery Panoply PostgreSQL Redshift
Release Status Open Beta Released Open Beta Released
Pricing Model Usage Storage Varies Hourly
Free Option No Yes (plan) Yes (self-hosted) Yes (plan & trial)
Database Type Analytic Analytic Transactional Analytic
Fully-Managed Yes Yes Depends No
Stitch Supports
Supported Versions n/a n/a 9.3+ n/a
Connection Methods SSL SSL SSH, SSL SSH, SSL
Incompatible Sources Yes Yes Yes Yes
Data Limits
Table Name Length 1,024 127 63 127
Column Name Length 128 115 59 115
Maximum # of Columns 10,000 1,600 250-1,600 1,600
Maximum VARCHAR Width None 65K None 65K
Nested Structure Support Native Support None None None
Case Insensitive Insensitive Sensitive Insensitive
Reserved Words Full List Full List Full List Full List

Additional Resources & Setup Tutorials

Ready to pick a destination and get started? Use the links below to check out a more in-depth look at each destination or move on to the setup and connection process.

BigQuery Panoply PostgreSQL Redshift

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Tags: destinations