Dataiku vs. Datameer

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Dataiku
Score 7.6 out of 10
N/A
The Dataiku platform unifies all data work, from analytics to Generative AI. It can modernize enterprise analytics and accelerate time to insights with visual, cloud-based tooling for data preparation, visualization, and workflow automation.N/A
Datameer
Score 8.4 out of 10
N/A
Datameer helps businesses clean up, combine, and organize data to make sense of it and use it for reports and machine learning.N/A
Pricing
DataikuDatameer
Editions & Modules
Discover
Contact sales team
Business
Contact sales team
Enterprise
Contact sales team
Team/Enterprise
Contact for pricing
per month Team
Offerings
Pricing Offerings
DataikuDatameer
Free Trial
YesYes
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
DataikuDatameer
Features
DataikuDatameer
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Dataiku
9.1
Ratings
8% above category average
Datameer
-
Ratings
Connect to Multiple Data Sources10.00 Ratings00 Ratings
Extend Existing Data Sources10.00 Ratings00 Ratings
Automatic Data Format Detection10.00 Ratings00 Ratings
MDM Integration6.50 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Dataiku
10.0
Ratings
18% above category average
Datameer
-
Ratings
Visualization9.90 Ratings00 Ratings
Interactive Data Analysis10.00 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Dataiku
10.0
Ratings
20% above category average
Datameer
-
Ratings
Interactive Data Cleaning and Enrichment10.00 Ratings00 Ratings
Data Transformations10.00 Ratings00 Ratings
Data Encryption10.00 Ratings00 Ratings
Built-in Processors10.00 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Dataiku
8.7
Ratings
4% above category average
Datameer
-
Ratings
Multiple Model Development Languages and Tools5.10 Ratings00 Ratings
Automated Machine Learning10.00 Ratings00 Ratings
Single platform for multiple model development10.00 Ratings00 Ratings
Self-Service Model Delivery10.00 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Dataiku
9.0
Ratings
5% above category average
Datameer
-
Ratings
Flexible Model Publishing Options9.00 Ratings00 Ratings
Security, Governance, and Cost Controls9.00 Ratings00 Ratings
Best Alternatives
DataikuDatameer
Small Businesses
Jupyter Notebook
Jupyter Notebook
Score 9.4 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.1 out of 10
Medium-sized Companies
Posit
Posit
Score 10.0 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
Enterprises
Posit
Posit
Score 10.0 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
DataikuDatameer
Likelihood to Recommend
10.0
(0 ratings)
9.0
(0 ratings)
Likelihood to Renew
-
(0 ratings)
6.4
(0 ratings)
Usability
10.0
(0 ratings)
9.0
(0 ratings)
Support Rating
9.4
(0 ratings)
8.0
(0 ratings)
User Testimonials
DataikuDatameer
Likelihood to Recommend
I would recommend it because it's an amazing tool for different levels of users. From Business Analysts to Data Scientists to Managers, various employees can make use of this tool to make data-driven decisions. I'm not sure about where it would be less appropriate as I'm using it as Data Scientist and so far it pretty much caters to my need.
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Datameer's workbooks include an intuitive GUI for maximum usability. Anyone with an analytical mind may easily compile data using the built-in worksheet capability without requiring much technological knowledge. Ad hoc reports may now be made and scheduled. In addition, I haven't had too much problem fixing things because I can get most of the answers I want there.
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Pros
  • Very intuitive and easy to use UI, making a lot of types of users can collaborate with each other easily, by visualizing the same workflow.
  • Many building blocks can be reused immediately, avoid a lot of non-standard boiler plate implementation.
  • Data pre-analysis and feature engineering assistance increase the productivity as well as the efficiency of data scientists.
  • Many data connectors support wide range of data storage, from SQL, TeraData, Hadoop Hive, etc.
  • Support from research till final MaaS solution deployment.
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  • It leverages scalability, flexibility and cost-effectiveness of hadoop to deliver an end-user focused analytic platform for big data without involvement of IT.
  • It overcomes Hadoop`s complexity by providing GUI interface with pre-built functions across integration, analytics and data visualization .
  • Excel feature is awesome for business users which is already provided by Datameer.
  • Using datameer now user can do smart analytic using Decision Trees, Column dependency and recommendation.
  • Recently HTML5 inclusion is making application to available on a wider range of devices, including the iPad and other mobile devices which does not support Flash.
  • It can be used in premise or in a cloud computing environment.
  • Wizard-based data integration designed for IT and business users to schedule and do transformation of large sets of structured, semi-structured and unstructured data without any knowledge of Hadoop ecosystem.
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Cons
  • Its community support is very limited at the moment
  • Complex to integrate with automation tools such as Blue Prism
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  • Data visualization and graphics. Right now it's not very user friendly. Creating dashboards requires a lot of work that can be done by the application
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Likelihood to Renew
No answers on this topic
Employees with intermediate SQL and Hive knowledge can generate reports faster than using Datameer . It does have visualization tool but I don't think it is anything that cannot be accomplished by importing the data in Excel
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Usability
As I have described earlier, the intuitiveness of this tool makes it great as well as the variety of users that can use this tool. Also, the plugins available in their repository provide solutions to various data science problems.
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Easy to use for most things, starts to require some planning as your projects get more complex.
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Support Rating
The open source user community is friendly, helpful, and responsive, at times even outdoing commercial software vendors. Documentation is also top notch, and usually resolves issues without the need for human interactions. Great product design, with a focus on user experience, also makes platform use intuitive, thus reducing the need for explicit support.
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No answers on this topic
Alternatives Considered
Strictly for Data Science operations, Anaconda can be considered as a subset of Dataiku DSS. While Anaconda supports Python and R programming languages, Dataiku also provides this facility, but also provides GUI to creates models with just a click of a button. This provides the flexibility to users who do not wish to alter the model hyperparameters in greater depths. Writing codes to extract meaningful data is time consuming compared to Dataiku's ability to perform feature engineering and data transformation through click of a button.
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I have compared Datameer with the tools listed above and it blows them out of the water. Datameer is much more user friendly than these tools and is also a lot more powerful. Once the Q1 release comes out with drill down capabilities on the infographics, Datameer will surpass Tableau and Spotfire in visualization.
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Return on Investment
  • Given its open source status, only cost is the learning curve, which is minimal compared to time savings for data exploration.
  • Platform also ease tracking of data processing workflow, unlike Excel.
  • Build-in data visualizations covers many use cases with minimal customization; time saver.
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  • Quick time to value. Transition from developer to learning Datameer is less than a day.
  • Workspace is drag and drop, which makes it intuitive and easy to use.
  • Speed of data transformations.
  • Pulling data from various sources.
  • Easy to schedule data pipelines.
  • Tailor made for Snowflake and Redshift.
  • Documentation is sometimes not updated quickly.
  • Training videos are a bit long.
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ScreenShots

Datameer Screenshots

Screenshot of DATA TRANSFORMATION: SQL or No Code

SQL SELECT statements can be used to explore and shape data. Work is represented visually on a canvas like interface, making it easier to design and maintain projects.

Datameer includes library of pre-built drag-and-drop transformations to accelerate SQL development or transform datasets without writing code.Screenshot of DATA CATALOG: Collaboration in Snowflake

Search, Metadata, Data Profiling, and Auto documentationScreenshot of AUTOMATION & INSIGHTS

Insights can be sent to email or Slack, integrated, and deployed to SnowflakeScreenshot of PRODUCTION PIPELINES: From ad-hoc exploration to production pipelines

GIT version control, materialization, dependency management, monitoring