Users report that Stitch excels in ease of use with a score of 9.4, making it a preferred choice for small businesses looking for a straightforward data integration solution. In contrast, Data Loader has a lower ease of use score of 7.9, which some users find less intuitive.
Reviewers mention that Stitch's extraction capabilities are particularly strong, scoring 9.1, which allows for efficient data retrieval from various sources. Data Loader, while competent, scores lower at 8.3, leading some users to feel it could improve in this area.
G2 users highlight Stitch's automation features, scoring 8.9, as a significant advantage, allowing for streamlined workflows. Data Loader, with a score of 7.7, is seen as less robust in automation, which can lead to more manual processes for users.
Reviewers say that Stitch's scalability is impressive, with a score of 8.6, making it suitable for growing businesses. Data Loader, scoring 7.7, may not scale as effectively, which could be a concern for users anticipating rapid growth.
Users on G2 report that Stitch's quality of support is rated at 8.7, with many praising the responsiveness and helpfulness of the support team. Data Loader's support, rated at 8.2, is seen as adequate but not as strong, leading to some user frustration during critical issues.
Reviewers mention that while both products have similar product direction scores of 8.1, Stitch's overall user satisfaction and positive feedback suggest a more favorable outlook for future updates and features compared to Data Loader.
Pricing
Entry-Level Pricing
Data Loader
No pricing available
Qlik Stitch
Standard Plans
$100/month up
based on volume above 5M rows/month
A flexible plan that grows with your needs. Full access to 100+ data sources.
We currently support over 100 SaaS data sources, and the complete list can be found at https://www.stitchdata.com/integrations/sources/ - if you don't find...Read more
Which data warehouses does Stitch support?
1 Comment
Official Response from Qlik Stitch
Currently, Stitch supports Amazon (Redshift & S3), Azure SQL, Google BigQuery, data.world, Panoply, PostgreSQL, and Snowflake ( see...Read more
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