Coginiti vs. Azure Data Lake Analytics

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Coginiti
Score 9.3 out of 10
N/A
Coginiti (formerly Aginity), the collaborative intelligence company, empowers users to get consistent answers to any business question. The Collaborative Intelligence platform provides a unique workspace that empowers the entire organization to build, share and reuse analytics. By making quality data widely available and focusing on outcomes over pre-defined output, everyone is freed up to explore and experiment to answer business questions. By creating and sharing both building blocks and…N/A
Azure Data Lake Analytics
Score 8.4 out of 10
N/A
Microsoft's Azure Data Lake Analytics is a BI service for processing big data jobs without consideration for infrastructure.N/A
Pricing
CoginitiAzure Data Lake Analytics
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
CoginitiAzure Data Lake Analytics
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
CoginitiAzure Data Lake Analytics
Top Pros
Top Cons
Best Alternatives
CoginitiAzure Data Lake Analytics
Small Businesses
Klipfolio
Klipfolio
Score 8.4 out of 10
Klipfolio
Klipfolio
Score 8.4 out of 10
Medium-sized Companies
Alteryx
Alteryx
Score 9.0 out of 10
Alteryx
Alteryx
Score 9.0 out of 10
Enterprises
Alteryx
Alteryx
Score 9.0 out of 10
Alteryx
Alteryx
Score 9.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
CoginitiAzure Data Lake Analytics
Likelihood to Recommend
9.3
(9 ratings)
8.7
(6 ratings)
User Testimonials
CoginitiAzure Data Lake Analytics
Likelihood to Recommend
Aginity
Aginity is able to track productivity which has been helping us be able to determine areas that need improvement. we have found agility very user-friendly in terms of ease of scalability. moreover, its ability to reuse SQL has saved us a lot of time because we do not have to re-code SQL.
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Microsoft
Azure Data Lake Analytics services are beneficial when working with a lot of data. It can process enormous amounts of data extremely quickly. Service is secure and easy to set up, build, scale, and run on Azure. Regarding big data analytics and reporting, parallel processing has a significant impact. It consolidated our analytics from multiple systems and increased our analysis productivity. This tool has excellent support for reporting tools like Power BI and is very quick when performing analytics.
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Pros
Aginity
  • Query auto-completion
  • Database exploration including schemas, tables, columns, distribution keys, sort keys, etc.
  • Common scenario query samples, and easy access to table DDL
  • Table size operational report
  • Free community edition
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Microsoft
  • Process large data transformation jobs using pretty much any language needed.
  • Native integration with Azure storage.
  • Top notch security that fulfills all audit needs.
  • Easy to consolidate enterprise data under one location - Single source of truth.
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Cons
Aginity
  • For one, I don't like how the parenthesis are automatically created as a set. Often times I only need to type one part of the parenthesis, but it creates a set of ( and ), forcing me to delete them because I didn't need the other half at where my cursor was. Same goes with any other sort of characters, such as ' '. I understand that it's suppose to be smart, but more often than not, it's causing more inconvenience and wasting more time, than actually saving time simply because it types an extra ) or ' for me.
  • The error message and the log. I would think there probably is a log somewhere, but the fact that I've been using Aginity for close to a year now, and I still haven't found something similar to a log, is saying something about this feature. A log is like a standard thing nowadays, for running codes, to check against what has happened with the code, and for debugging what you have done wrong within the code. It also contains error messages, and help you troubleshoot with a clearer picture. The error message display current is very small and hard to read, sometimes the error message itself is not as easy to understand either. I use SAS on a daily basis as well, I feel like SAS has done a way better job on this issue, than Aginity.
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Microsoft
  • There's a bit of bias towards cloud with ADL Analytics. Depending upon a company's infra strategy and investment plans, there are some challenges with migration and integeration.
  • Not worth the time/effort/money if the organization doesn't have "Volume" of data. Cost effective only when daily loads exceed around 1million.
  • While training materials are available online, Adoption rate - Yet to pick up.
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Alternatives Considered
Aginity
Aginity offers the best tools for data research, which are easy to use and customize. Unlike Aginity, AdvancedMiner wasn't only hard to deploy but also was highly-priced.
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Microsoft
We did some research about Alibaba Cloud Data Lake Analytics and even being cheaper than Azure Data Lake Analytics, we decided to go for the second one once we noticed they have more features and better documentation. Another thing we considered during this process was the fact that we have more people that already have Azure Cloud knowledge.
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Return on Investment
Aginity
  • We are able to create analytics without needing programming skills.
  • Query auto-completion.
  • Database exploration includes schemas, tables, columns, distribution keys, sort keys, and so forth.
  • Attractive GUI and easy to navigate for easy data reporting.
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Microsoft
  • It lets us manage and scan data, making our work easy and efficient.
  • It helped me manage real-time data, process it, and send it to reporting.
  • Data centralization or data warehousing projects are being implemented with its help.
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ScreenShots