Actian Ingres vs Databricks comparison

The compared Actian and Databricks solutions aren't in the same category. Actian is ranked #22 in Data Warehouse , and holds a 0.6% mindshare in the category. Databricks is ranked #1 in Data Science Platforms , with an average rating of 8.2, and holds a 19.1% mindshare. Additionally, 100% of Actian users are willing to recommend the solution, compared to 96% of Databricks users who would recommend it.

Actian Ingres

Read 1 Actian Ingres review

315 Views
163 Comparison Views

100% willing to recommend

Databricks

Read 82 Databricks reviews

19,952 Views
13,156 Comparison Views

96% willing to recommend

Actian Ingres

Databricks

Comparison Buyer's Guide

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Executive Summary

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

Find out what your peers are saying about Snowflake Computing, Oracle, Teradata and others in Data Warehouse.

To learn more, read our detailed Data Warehouse Report (Updated: October 2024).

Buyer's Guide

Data Warehouse

October 2024

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Helped 814,763 peers since 2012

Categories and Ranking

Actian Ingres

Average Rating

9.0

Number of Reviews

Ranking in other categories

Data Warehouse (22nd)

Databricks

Average Rating

8.2

Number of Reviews

Ranking in other categories

Data Science Platforms (1st), Streaming Analytics (1st)

Mindshare comparison

Actian Ingres and Databricks aren’t in the same category and serve different purposes. Actian Ingres is designed for Data Warehouse and holds a mindshare of 0.6%, up 0.6% compared to last year.
Databricks, on the other hand, focuses on Data Science Platforms, holds 19.1% mindshare, up 19.1% since last year.

Data Warehouse

Data Science Platforms

Featured Reviews

Edward Griffiths

Managing Director at Jet iT Ltd.

Jan 28, 2021

Good multi-platform SQL compatibility, as well as performance and data integrity

We currently run Web server solutions (CMS, CRM business solutions). Our CMS solution is obviously very text-oriented, and our CRM Business Solution was built for a finance and asset management business, which is capable of handling millions of transactions. Performance, access control, data…

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Dunstan Matekenya

Data Scientist at a financial services firm with 10,001+ employees

Jul 10, 2024

Process large-scale data sets and integrates with Apache Spark with notebook environment

I primarily use Databricks to process large-scale data sets with Apache Spark. My main use case is processing large data sets, such as 600 GB or 800 GB Databricks integrates natively with Apache Spark, which I use as a processing engine for large-scale datasets. This native integration is one of…

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Quotes from Members

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

Pros

"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."

"Specifically for data science and data analytics purposes, it can handle large amounts of data in less time. I can compare it with Teradata. If a job takes five hours with Teradata databases, Databricks can complete it in around three to three and a half hours."

"Databricks has a scalable Spark cluster creation process. The creators of Databricks are also the creators of Spark, and they are the industry leaders in terms of performance."

"The processing capacity is tremendous in the database."

"The most valuable feature of Databricks is the notebook, data factory, and ease of use."

"We have the ability to scale, collaborate and do machine learning."

"The load distribution capabilities are good, and you can perform data processing tasks very quickly."

"Databricks integrates well with other solutions."

"Databricks has helped us have a good presence in data."

More Databricks pros

Cons

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

"The product could be improved regarding the delay when switching to higher-performing virtual machines compared to other platforms."

"The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."

"There could be more support for automated machine learning in the database. I would like to see more ways to do analysis so that the reporting is more understandable."

"When I used the support, I had communication problems because of the language barrier with the agent. The accent was difficult to understand."

"In the future, I would like to see Data Lake support. That is something that I'm looking forward to."

"Databricks could improve in some of its functionality."

"The integration of data could be a bit better."

"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."

More Databricks cons

Pricing and Cost Advice

Information not available

"We implement this solution on behalf of our customers who have their own Azure subscription and they pay for Databricks themselves. The pricing is more expensive if you have large volumes of data."

"The billing of Databricks can be difficult and should improve."

"The licensing costs of Databricks is a tiered licensing regime, so it is flexible."

"I would rate the tool’s pricing an eight out of ten."

"I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."

"The product pricing is moderate."

"The solution requires a subscription."

"Whenever we want to find the actual costing, we have to send an email to Databricks, so having the information available on the internet would be helpful."

More Databricks pricing and cost advice

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Top Industries

By visitors reading reviews

Computer Software Company

25%

Government

11%

Manufacturing Company

Educational Organization

Financial Services Firm

16%

Computer Software Company

12%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

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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 ...

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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...

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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...

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Comparisons

Oracle Database Appliance vs Actian Ingres

Compared 37% of the time

Teradata vs Actian Ingres

Compared 32% of the time

Snowflake vs Actian Ingres

Compared 32% of the time

More Actian Ingres Competitors

Dataiku vs Databricks

Compared 11% of the time

Informatica PowerCenter vs Databricks

Compared 8% of the time

Amazon SageMaker vs Databricks

Compared 8% of the time

Dremio vs Databricks

Compared 8% of the time

Microsoft Power BI vs Databricks

Compared 6% of the time

More Databricks Competitors

Product Reports

Buyer's Guide

Data Warehouse

October 2024

Download Actian Ingres product report

Buyer's Guide

Databricks

November 2024

Download Databricks product report

Also Known As

Ingres, Ingres 2006

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

Learn More

Video not available

Actian

Databricks

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.

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

Find out what your peers are saying about Snowflake Computing, Oracle, Teradata and others in Data Warehouse. Updated: October 2024.

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We monitor all Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.