TrustRadius

Cinchy vs. Databricks Data Intelligence Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Cinchy
Score 0.0 out of 10
N/A
The Cinchy Data Collaboration Platform liberates data from applications and allows for the management and control data as products, eliminating the need for future data integration. This is to support a more agile data ecosystem that makes change simple, rapidly accelerates business outcomes and fosters collaborative intelligence across the enterprise.N/A
Databricks Data Intelligence Platform
Score 8.5 out of 10
N/A
Databricks in San Francisco offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service aims to provide a reliable and scalable platform for data pipelines, data lakes, and data platforms. Users can manage full data journey, to ingest, process, store, and expose data throughout an organization. Its Data Science Workspace is a collaborative environment for practitioners to run…
$0.07
Per DBU
Pricing
CinchyDatabricks Data Intelligence Platform
Editions & Modules
No answers on this topic
Standard
$0.07
Per DBU
Premium
$0.10
Per DBU
Enterprise
$0.13
Per DBU
Offerings
Pricing Offerings
CinchyDatabricks Data Intelligence Platform
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
CinchyDatabricks Data Intelligence Platform
Best Alternatives
CinchyDatabricks Data Intelligence Platform
Small Businesses
DBeaver
DBeaver
Score 9.2 out of 10

No answers on this topic

Medium-sized Companies
DBeaver
DBeaver
Score 9.2 out of 10
Snowflake
Snowflake
Score 8.9 out of 10
Enterprises
DBeaver
DBeaver
Score 9.2 out of 10
Snowflake
Snowflake
Score 8.9 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
CinchyDatabricks Data Intelligence Platform
Likelihood to Recommend
-
(0 ratings)
10.0
(0 ratings)
Usability
-
(0 ratings)
10.0
(0 ratings)
Support Rating
-
(0 ratings)
8.7
(0 ratings)
User Testimonials
CinchyDatabricks Data Intelligence Platform
Likelihood to Recommend
No answers on this topic
If you need a managed big data megastore, which has native integration with highly optimized Apache Spark Engine and native integration with MLflow, go for Databricks Lakehouse Platform. The Databricks Lakehouse Platform is a breeze to use and analytics capabilities are supported out of the box. You will find it a bit difficult to manage code in notebooks but you will get used to it soon.
Verified User
Anonymous
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Pros
No answers on this topic
  • There is databricks community, which is a free version. It is available for beginners to have an easy start with a big data platform. It does not have every feature of the full version but is still adequate for extremely new coders.
  • There are many resourceful training elements that are available to developers, data scientists, data engineers and other IT professionals to learn Apache Spark.
Ann Le | TrustRadius Reviewer
Ann Le
Freelance Translator
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Cons
No answers on this topic
  • Connect my local code in Visual code to my Databricks Lakehouse Platform cluster so I can run the code on the cluster. The old databricks-connect approach has many bugs and is hard to set up. The new Databricks Lakehouse Platform extension on Visual Code, doesn't allow the developers to debug their code line by line (only we can run the code).
  • Maybe have a specific Databricks Lakehouse Platform IDE that can be used by Databricks Lakehouse Platform users to develop locally.
  • Visualization in MLFLOW experiment can be enhanced
Verified User
Anonymous
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Usability
No answers on this topic
Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.

in terms of graph generation and interaction it could improve their UI and UX
Verified User
Anonymous
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Support Rating
No answers on this topic
One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.
Jonatan Bouchard | TrustRadius Reviewer
Jonatan Bouchard
Director Data Science
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Alternatives Considered
No answers on this topic
Databricks is a true all-in-one platform, and at the time of implementation, it had more features available to us, making it a clear choice over Snowflake. Moving our workloads from local computing to the servers in Databricks gave our start-up staff a great quality of life boost.
Austin Franchino | TrustRadius Reviewer
Austin Franchino
Senior Data and Security Engineer
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Return on Investment
No answers on this topic
  • ROI for us has been tremendous. Time to market by processing raw data in our big data infrastructure has been pretty fast.
  • Non engineers can easily use Databricks, hence helping business customers.
  • Thousands of different data combinations can easily be joined and used by our data teams.
Verified User
Anonymous
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ScreenShots

Cinchy Screenshots

Screenshot of A single UI to view and manage data - The universal Data Browser to view, change, analyze, and otherwise interact with data on the Fabric. Non-technical business users can manage and update data, build models, and set controls, all through its UI.Screenshot of Data is managed and protected down to the individual cell - Data on the Autonomous Data Fabric is protected by cellular-level access controls, data-driven entitlements, and data governance. This includes meta architecture, versioning, and write-specific business functions that restrict user views, such as a managed hierarchy. Owner-defined permissions are universally enforced, to reduce the effort of managing them at the enterprise level. Existing Active Directory and SSO access policies can be used to set controls for an individual user, external system, or user-defined functions (such as approving updates row by row or using bulk approvals).