Stitch Reviews

5 Ratings
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Score 7.6 out of 101

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Score 7 out of 10
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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.
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January 31, 2018

A time saver

Score 9 out of 10
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Stitch is used by the data team which is mainly the BI analyst, the lead developer, the CFO and the web analytics person. We all need the data from our third-party tools but do not have the time/skills/will to build and manage integrations.
  • Stitch does one thing and does it well: turn the data ingestion from third-party APIs into a one-click task
  • It makes all that data into a proper schema as a bonus
  • One of our integrations had to be re-synced on a regular basis. I still don't know why.
It is well suited for a startup that does not want to pay a developer/data engineer to develop and monitor third-party API integrations but wants nonetheless to exploit all the insights in the data.

Stitch charges based on the volume of data imported. At some point it is probably cheaper to hire someone to build the integrations in-house.

It is not suited for a big company for which ETL is a really big thing and does not want to outsource it.
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About Stitch

Stitch in Philadelphia offers their flagship ETL tool to developers; the company was spun off from RJMetrics after that company's acquisition by Magento, and is an independent entity.
Categories:  Data Warehouse

Stitch Technical Details

Operating Systems: Unspecified
Mobile Application:No