Likelihood to Recommend One of AWS Glue's most notable features that aid in the creation and transformation of data is its data catalog. Support, scheduling, and the automation of the data schema recognition make it superior to its competitors aside from that. It also integrates perfectly with other AWS tools. The main restriction may be integrated with systems outside of the AWS environment. It functions flawlessly with the current AWS services but not with other goods. Another potential restriction that comes to mind is that glue operates on a spark, which means the engineer needs to be conversant in the language.
Read full review Dataiku DSS is very well suited to handle large datasets and projects which requires a huge team to deliver results. This allows users to collaborate with each other while working on individual tasks. The workflow is easily streamlined and every action is backed up, allowing users to revert to specific tasks whenever required. While Dataiku DSS works seamlessly with all types of projects dealing with structured datasets, I haven't come across projects using Dataiku dealing with images/audio signals. But a workaround would be to store the images as vectors and perform the necessary tasks.
Read full review Pros It is extremely fast, easy, and self-intuitive. Though it is a suite of services, it requires pretty less time to get control over it. As it is a managed service, one need not take care of a lot of underlying details. The identification of data schema, code generation, customization, and orchestration of the different job components allows the developers to focus on the core business problem without worrying about infrastructure issues. It is a pay-as-you-go service. So, there is no need to provide any capacity in advance. So, it makes scheduling much easier. Read full review The intuitiveness of this tool is very good. Click or Code - If you are a coder, you can code. If you are a manager, you can wrangle with data with visuals The way you can control things, the set of APIs gives a lot of flexibility to a developer. Read full review Cons In-Stream schema registries feature people can not use this more efficiently in Connections feature they can add more connectors as well The crucial problem with AWS Glue is that it only works with AWS. Read full review Read full review 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.
Read full review Support Rating Amazon responds in good time once the ticket has been generated but needs to generate tickets frequent because very few sample codes are available, and it's not cover all the scenarios.
Read full review The support team is very helpful, and even when we discover the missing features, after providing enough rational reasons and requirements, they put into it their development pipeline for the future release.
Read full review Alternatives Considered AWS Glue is a fully managed ETL service that automates many ETL tasks, making it easier to set AWS Glue simplifies ETL through a visual interface and automated code generation.
Read full review 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.
Read full review Return on Investment It had a positive impact on the way we build our data lake. It is the single source of truth for data structure (schemas/tables/views). Read full review 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. Read full review ScreenShots