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Stitch from Talend

Stitch from Talend


What is Stitch from Talend?

Stitch, or Stitch Data, now from Talend (acquired in late 2018) is an ETL tool for developers; the company was spun off from RJMetrics after that company's acquisition by Magento. Talend describes Stitch as a cloud-first, open source platform for…

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Recent Reviews

TrustRadius Insights

The Stitch has established itself as a reliable tool for efficiently building data pipelines. Many users consider The Stitch their go-to …
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Product Details

Stitch from Talend Technical Details

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Mobile ApplicationNo
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Reviews and Ratings


Community Insights

TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!

The Stitch has established itself as a reliable tool for efficiently building data pipelines. Many users consider The Stitch their go-to choice for an ETL tool and only explore other options when absolutely necessary. While some users have mentioned certain missing features, overall, The Stitch provides a satisfactory experience. Both engineering and data teams rely on The Stitch to replicate transactional datastores to an analytics warehouse. Users particularly appreciate that The Stitch supports the extraction, transformation, and loading of data into different schemas and data types, which is crucial for supporting data and BI teams. Furthermore, the singer-based architecture of The Stitch allows for extending integration capabilities beyond the provided connectors. The Ops team also leverages The Stitch to automate tasks and access data for dashboards, such as migrating data from Google Sheets to the database.


(1-4 of 4)
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Score 6 out of 10
Vetted Review
Verified User
We use Stitch from Talend to get data from a variety of platforms into our data warehouse without having to deal with APIs (as I am not a developer). There are many integration options and data is able to be imported into our data warehouse without the need for heavy lifting on the development side. We then use the integrations within Stitch from Talend to get data from the data sources to our data warehouse, GCP BigQuery.
  • Integrations
  • Customer Support
  • Set up and management
  • Pricing
  • Transparency
  • Annual vs. Monthly Contracts
  • Version control for Integrations
  • Documentation
  • Communication of deprecations/upgrades that require work/adjustments
Stitch from Talend is very well suited for companies or individuals who have little to no development resources and need to get data from various platforms into a data warehouse. It is one of the more affordable options available. It's also useful to use Stitch from Talend as a hub for a custom webhook if there is a desire to keep all integrations in one place and maintain formatting once in the data warehouse.
  • KPI Management
  • Data Visualization
  • Data sanitization/normalization
  • Ease of ETL process
Stitch from Talend is way more cost effective and has a business model that better aligns with our company. From what I can tell Stitch from Talend has a better customer support platform as well and has been very easy to work with when issues have come up. They also seem less pushy when it comes to sales.
Jono Child | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Stitch is used by the Data team and our Ops teams. The data team uses it for major apis like google ads, Facebook, Salesforce or Intercom to pass data to our warehouse in an easy automated way.

Our Ops team use it to pass data entry from Google sheets to the database to automate tasks or have data for dashboards.
  • Automate data ingestion.
  • Better error messages so you can determine what the problem is.
Stitch is very cheap and useful for small to medium size companies to ingest data from common apis/platforms in a quick and cheap way.
  • Good ROI in terms of being able to monitor cost performance from Google, Facebook, etc.
  • Easy to have Salesforce data and Intercom data for dashboards.
Stitch is much cheaper and probably simpler than tools like Fivetran. Stitch is for simpler projects and used alongside traditional ETL and writing ones own code into APIs.
Fivetran is more of a overarching tool but also more expensive
Score 7 out of 10
Vetted Review
Verified User
We use Stitch, [a Talend company] and Fivetran to ingest data in our snowflake data warehouse. This allows us to allow our users perform ingestion so we can take care of transformations and platform building which are more technical work. We like Stitch's singer based architecture which allows you to extend integration capabilities beyond connectors provided.
  • Easy integration with many sources
  • Extensible
  • Not as expensive as Fivetran
  • Users feel the UI is not as friendly
Ingestion tools make life easy to ingest new data sources. However, they are single tool in your tool box and treat them as such. They won't do your transformations nor do they (neither should they) have ability to define dependencies. They are built for making your ingestions mindlessly simple.
  • Freed up data engineers to work on transformations
  • Bought us some time to migrate from our ETL tool
We use both
Score 7 out of 10
Vetted Review
Verified User
We use Stitch to periodically replicate transactional datastores to an analytics warehouse. The transactional datastore are primarily PostgreSQL and MongoDB databases for microservices. Both the engineering and data teams use Stitch. The transactional datastores are not suitable for running analytics queries; they are tuned for different types of queries and access patterns. Extracting data from the transactional stores, transforming it to a different schema and data types, and loading it into a different datastore is not trivial work, and it is necessary to support the data and BI teams.
  • Stitch is good at replicating relational databases. It manages the conversion of data types and schemas, and it is capable of incremental replication.
  • Stitch's UI makes it easy to configure which tables should be replicated, and how they should be replicated.
  • Stitch is not good at replicating document stores like MongoDB to relational databases. To be fair, this is a difficult task. Stitch flattens the objects, but the result is unwieldy.
  • Stitch cannot replicate the same source to multiple sinks, which is inconvenient if you want to replicate some of a datastore's tables to Redshift and others to Redshift Spectrum, for instance.
Stitch is great for small organizations who want their data and business intelligence organizations to focus on building competitive advantages instead of building data pipelines. AWS DMS offers continuous replication and greater flexibility, if you have the engineering resources to configure it. Stitch may be too inflexible for large organizations with a variety of needs.
  • Stitch manages replication of transactional datastores to our data warehouse. Our data and business intelligence teams need this data to be replicated. Stitch allows our data engineers to focus on our product.
Stitch is less flexible than AWS DMS, but it is fully-managed.
Our organization has Stitch users on the data science, engineering, and business intelligence teams.
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