What is Stitch?
Who uses Stitch?
Here are some stack decisions, common use cases and reviews by companies and developers who chose Stitch in their tech stack.
Looker , Stitch , Amazon Redshift , dbt
We recently moved our Data Analytics and Business Intelligence tooling to Looker . It's already helping us create a solid process for reusable SQL-based data modeling, with consistent definitions across the entire organizations. Looker allows us to collaboratively build these version-controlled models and push the limits of what we've traditionally been able to accomplish with analytics with a lean team.
For Data Engineering, we're in the process of moving from maintaining our own ETL pipelines on AWS to a managed ELT system on Stitch. We're also evaluating the command line tool, dbt to manage data transformations. Our hope is that Stitch + dbt will streamline the ELT bit, allowing us to focus our energies on analyzing data, rather than managing it.
Multiple systems means there is a requirement to cart data across them.
Started off with Talend scripts. This was great as what we initially had were PHP/Python script - allowed for a more systematic approach to ETL.
But ended up with a massive repository of scripts, complex crontab entries and regular failures due to memory issues.
Using Stitch or similar services is a better approach: - no need to worry about the infrastructure needed for the ETL processes - a more formal mapping of data from source to destination as opposed to script developer doing his/her voodoo magic - lot of common sources and destination integrations are already builtin and out of the box Stitch
- Connect to your ecosystem of data sources - UI allows you to configure your data pipeline in a way that balances data freshness with cost and production database load
- Replication frequency - Choose full or incremental loads, and determine how often you want them to run - from every minute, to once every 24 hours
- Data selection - Configure exactly what data gets replicated by selecting the tables, fields, collections, and endpoints you want in your warehouse
- API - With the Stitch API, you're free to replicate data from any source. Its REST API supports JSON or Transit, and recognizes your schema based on the data you send.
- Usage dashboard - Access our simple UI to check usage data like the number of rows synced by data source, and how you're pacing toward your monthly row limit
- Email alerts - Receive immediate notifications when Stitch encounters issues like expired credentials, integration updates, or warehouse errors preventing loads
- Warehouse views - By using the freshness data provided by Stitch, you can build a simple audit table to track replication frequency
- Scalable - Highly Scalable Stitch handles all data volumes with no data caps, allowing you to grow without the possibility of an ETL failure
- Transform nested JSON - Stitch provides automatic detection and normalization of nested document structures into relational schemas
- Complete historical data - On your first sync, Stitch replicates all available historical data from your database and SaaS tools. No database dump necessary.