Best Relational Database for TensorFlow
View:
Compare the Top Relational Database that integrates with TensorFlow as of November 2025
Sort By:
This a list of Relational Database that integrates with TensorFlow. Use the filters on the left to add additional filters for products that have integrations with TensorFlow. View the products that work with TensorFlow in the table below.
What is Relational Database for TensorFlow?
Relational database software provides users with the tools to capture, store, search, retrieve and manage information in data points related to one another. Compare and read user reviews of the best Relational Database for TensorFlow currently available using the table below. This list is updated regularly.
-
1
LeanXcale
LeanXcale
LeanXcale is a fast and scalable database that combines the characteristics of SQL and NoSQL. It is built to ingest massive batch and real-time data pipelines and make it available through SQL or GIS for any use, such as operational applications, analytics, dashboarding, or machine learning processing. No matter what stack you use, LeanXcale provides you both SQL and NoSQL interfaces. KiVi storage engine is a relational key-value data store. Users can access the data not only through the standard SQL API but also through a direct ACID key-value interface. This key-value interface allows users to perform data ingestion at very high rates and very efficiently by avoiding SQL processing overhead. Highly-scalable, efficient and distributed storage engine distributed data along the cluster to improve the performance and increase the reliability.Starting Price: $0.127 per GB per month
- Previous
- You're on page 1
- Next
