We performed a comparison between AWS Glue and Elastic Search based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Glue is a NoSQL-based data ETL tool that has some advantages over IIS and ISAs."
"One of the best features of the solution is its ability to easily integrate with other AWS services."
"I like its integration and ability to handle all data-related tasks."
"The most valuable features currently are glue studio, jobs, and triggers."
"It is AWS-integrated. There is end-to-end integration with the other AWS services. It is also user-friendly."
"AWS Glue is quite better than other tools, but you have to learn it properly before you start using it."
"The key role for Glue is that it hosts our metadata before rolling out our actual data. This is the major advantage of using this solution and our clients client have been very satisfied with it."
"The most valuable feature of AWS Glue is scalability."
"The most valuable feature for us is the analytics that we can configure and view using Kibana."
"You have dashboards, it is visual, there are maps, you can create canvases. It's more visual than anything that I've ever used."
"X-Pack provides good features, like authorization and alerts."
"Gives us a more user-friendly, centralized solution (for those who just needed a quick glance, without being masters of sed and awk) as well as the ability to implement various mechanisms for machine-learning from our logs, and sending alerts for anomalies."
"The initial installation and setup were straightforward."
"Elastic Enterprise Search is scalable. On a scale of one to 10, with one being not scalable and 10 being very scalable, I give Elastic Enterprise Search a 10."
"The solution offers good stability."
"The product is scalable with good performance."
"The crucial problem with AWS Glue is that it only works with AWS. It is not an agnostic tool like Pentaho. In PowerCenter, we can install the forms from Google and other vendors, but in the case of AWS Glue, we can only use AWS."
"The solution’s stability could be improved."
"Cost-wise, AWS Glue is expensive, so that's an area for improvement. The process for setting up the solution was also complex, which is another area for improvement."
"It would be better if it were more user-friendly. The interesting thing we found is that it was a little strange at the beginning. The way Glue works is not very straightforward. After trying different things, for example, we used just the console to create jobs. Then we realized that things were not working as expected. After researching and learning more, we realized that even though the console creates the script for the ETL processes, you need to modify or write your own script in Spark to do everything you want it to do. For example, we are pulling data from our source database and our application database, which is in Aurora. From there, we are doing the ETL to transform the data and write the results into Redshift. But what was surprising is that it's almost like whatever you want to do, you can do it with Glue because you have the option to put together your own script. Even though there are many functionalities and many connections, you have the opportunity to write your own queries to do whatever transformations you need to do. It's a little deceiving that some options are supposed to work in a certain way when you set them up in the console, but then they are not exactly working the right way or not as expected. It would be better if they provided more examples and more documentation on options."
"AWS Glue is more costly compared to other tools like Airflow."
"It is not clear how the partition discovery would have been affected by more data coming in."
"The solution should offer features for streaming data in addition to batching data."
"I would like to see stable libraries at the moment they are not there."
"Improving machine learning capabilities would be beneficial."
"We see the need for some improvements with Elasticsearch. We would like the Elasticsearch package to include training lessons for our staff."
"It was not possible to use authentication three years back. You needed to buy the product's services for authentication."
"The metadata gets stored along with indexes and isn't queryable."
"Better dashboards or a better configuration system would be very good."
"The documentation regarding customization could be better."
"The solution has quite a steep learning curve. The usability and general user-friendliness could be improved. However, that is kind of typical with products that have a lot of flexibility, or a lot of capabilities. Sometimes having more choices makes things more complex. It makes it difficult to configure it, though. It's kind of a bitter pill that you have to swallow in the beginning and you really have to get through it."
"This product could be improved with additional security, and the addition of support for machine learning devices."
AWS Glue is ranked 1st in Cloud Data Integration with 37 reviews while Elastic Search is ranked 10th in Cloud Data Integration with 59 reviews. AWS Glue is rated 7.8, while Elastic Search is rated 8.2. The top reviewer of AWS Glue writes "Provides serverless mechanism, easy data transformation and automated infrastructure management". On the other hand, the top reviewer of Elastic Search writes "Played a crucial role in enhancing our cybersecurity efforts ". AWS Glue is most compared with AWS Database Migration Service, Informatica PowerCenter, Informatica Cloud Data Integration, SSIS and Talend Open Studio, whereas Elastic Search is most compared with Faiss, Milvus, Pinecone, Azure Search and Amazon Kendra. See our AWS Glue vs. Elastic Search report.
See our list of best Cloud Data Integration vendors.
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