Altiscale vs Stitch: What are the differences?
What is Altiscale? Hadoop as a Service. we run Apache Hadoop for you. We not only deploy Hadoop, we monitor, manage, fix, and update it for you. Then we take it a step further: We monitor your jobs, notify you when something’s wrong with them, and can help with tuning.
What is Stitch? All your data. In your data warehouse. In minutes. Stitch is a simple, powerful ETL service built for software developers. Stitch evolved out of RJMetrics, a widely used business intelligence platform. When RJMetrics was acquired by Magento in 2016, Stitch was launched as its own company.
Altiscale and Stitch can be primarily classified as "Big Data as a Service" tools.
Some of the features offered by Altiscale are:
- Hadoop Dialtone
- “Infinite” Hadoop
- A Proactive Hadoop Helpdesk
On the other hand, Stitch provides the following key features:
- 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
"Our data sci & analysts would scream if went back toEMR" is the top reason why over 2 developers like Altiscale, while over 5 developers mention "3 minutes to set up" as the leading cause for choosing Stitch.
What is Altiscale?
What is Stitch?
Need advice about which tool to choose?Ask the StackShare community!
Why do developers choose Altiscale?
Sign up to add, upvote and see more prosMake informed product decisions
What are the cons of using Altiscale?
What are the cons of using Stitch?
Sign up to get full access to all the companiesMake informed product decisions
What tools integrate with Altiscale?
Sign up to get full access to all the tool integrationsMake informed product decisions
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.