Actian Ingres vs Databricks comparison

Read 91 Databricks reviews

25,542 Views
2,043 Comparison Views

96% willing to recommend

Actian Ingres

Comparison Buyer's Guide

Download the report

Executive Summary

We performed a comparison between Actian Ingres and Databricks based on real PeerSpot user reviews.

Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Actian Ingres vs. Databricks Report (Updated: July 2025).

Actian Ingres vs. Databricks

July 2025

Download the complete report

Helped 862,624 peers since 2012

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Actian Ingres

Average Rating

8.6

Reviews Sentiment

7.9

Number of Reviews

Ranking in other categories

Relational Databases Tools (26th), Data Warehouse (16th)

Databricks

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (8th), Data Science Platforms (1st), Streaming Analytics (1st)

Featured Reviews

GustavHoltzhausen

Sr Sales Engineer at HCLSoftware

Reliable performance enhances operations with good technical support

We run the entire IRS system, the income system, and the tax system. We also manage the entire Absa banking system in Africa. There's a lot of database applications, similar to those used in banks and the IRS The most valuable features for us are reliability and performance. Our system is used…

Read full review

ShubhamSharma7

Data Engineer at a engineering company with 1,001-5,000 employees

Capability to integrate diverse coding languages in a single notebook greatly enhances workflow

Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.

Read full review

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The most valuable features for us are reliability and performance."

"The deployment of our solution across a number of servers using Ingres .NET has meant that we can protect the database server behind a highly secure firewall and deploy the front end solutions on a normal web server."

"The solution offers a free community version."

"Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions."

"I like how easy it is to share your notebook with others. You can give people permission to read or edit. I think that's a great feature. You can also pull in code from GitHub pretty easily. I didn't use it that often, but I think that's a cool feature."

"The solution is an impressive tool for data migration and integration."

"The most valuable feature of Databricks is the integration with Microsoft Azure."

"The most valuable feature is the ability to use SQL directly with Databricks."

"The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes."

"The initial setup phase of Databricks was good."

More Databricks pros

Cons

"The seamless integration is a bit of an issue."

"The ability to reset the log file without stopping the DBMS would be helpful for us."

"The product should incorporate more learning aspects. It needs to have a free trial version that the team can practice."

"The initial setup of Databricks could be complex."

"The query plan is not easy with Databrick's job level. If I want to tune any of the code, it is not easily available in the blogs as well."

"While Databricks is generally a robust solution, I have noticed a limitation with debugging in the Delta Live Table, which could be improved."

"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."

"We often use a single cluster to ingest Databricks, which Databricks doesn't recommend. They suggest using a no-cluster solution like job clusters. This can be overwhelming for us because we started smaller."

"It would be better if it were faster. It can be slow, and it can be super fast for big data. But for small data, sometimes there is a sub-second response, which can be considered slow. In the next release, I would like to have automatic creation of APIs because they don't have it at the moment, and I spend a lot of time building them."

"As a data engineer, I see cluster failure in our Databricks user databases as a major issue."

More Databricks cons

Pricing and Cost Advice

Information not available

"My smallest project is around a hundred euros, and my most expensive is just under a thousand euros a week. That is based on terabytes of data processed each month."

"The price is okay. It's competitive."

"The solution requires a subscription."

"I would rate Databricks' pricing seven out of ten."

"Price-wise, I would rate Databricks a three out of five."

"I'm not involved in the financing, but I can say that the solution seemed reasonably priced compared to the competitors. Similar products are usually in the same price range. With five being affordable and one being expensive, I would rate Databricks a four out of five."

"The basic version of this solution is now open-source, so there are no license costs involved. However, there is a charge for any advanced functionality and this can be quite expensive."

"The licensing costs of Databricks depend on how many licenses we need, depending on which Databricks provides a lot of discounts."

More Databricks pricing and cost advice

See which vendors are best for you

Use our free recommendation engine to learn which Cloud Data Warehouse solutions are best for your needs.

See recommendations

862,624 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Computer Software Company

24%

Insurance Company

University

Government

Financial Services Firm

17%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What needs improvement with Actian Ingres?

The seamless integration is a bit of an issue. I would like to see more direct connectors and stuff like SQLAlchemy. It's there but isn't available as a standard, so it involves going to GitHub to ...

What is your primary use case for Actian Ingres?

What is your experience regarding pricing and costs for Actian Ingres?

Initially, it's a lot less expensive than competitors. Price performance has always been a priority, ensuring we remain competitive in the market.

Which do you prefer - Databricks or Azure Machine Learning Studio?

Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...

How would you compare Databricks vs Amazon SageMaker?

We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...

Which would you choose - Databricks or Azure Stream Analytics?

Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...

Oracle Database Appliance vs Actian Ingres

Comparisons

Compared 59% of the time

Snowflake vs Actian Ingres

Compared 41% of the time

More Actian Ingres Competitors

Dataiku vs Databricks

Compared 10% of the time

Microsoft Power BI vs Databricks

Compared 9% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Dremio vs Databricks

Compared 6% of the time

Tableau vs Databricks

Compared 5% of the time

More Databricks Competitors

Product Reports

Download Actian Ingres product report

Data Warehouse

June 2025

Download Databricks product report

July 2025

Also Known As

Ingres, Ingres 2006

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

Overview

Actian’s Ingres is a leading, enterprise-grade database management system designed to reduce IT costs and time-to-value, while delivering the strength and features expected from an enterprise-class database. Ingres 10.2 is the latest version of the database, containing enhancements that will make it easier to internationalize customer applications. Along with improved performance and reduced configuration overhead, users can take their first steps into big data analytics with the new Window functions.

Actian

Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.

Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.

What are the key features of Databricks?

User-friendly interface: Simplifies operations and usability.
Built-in machine learning libraries: Facilitates machine learning tasks.
Support for multiple programming languages: Enhances flexibility.
Scalability: Efficiently handles growing data needs.
Fast processing: Improves performance and speed.
Automated optimization: Reduces manual efforts.
Data visualization: Provides insightful visuals.
Collaborative features: Enhances teamwork.
Delta Lake performance: Boosts data management.
Seamless cluster management: Simplifies system operations.

What are the benefits or ROI to look for in Databricks reviews?

Efficiency in handling large datasets: Ensures smooth processing.
Interactive workspace environment: Improves user collaboration.
Integration with platforms: Provides connectivity benefits.
Performance optimization: Enhances overall system performance.
Support for data governance and security: Ensures data integrity and protection.

Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.

Sample Customers

Groupe Adeo, IsCool Entertainment

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware