AWS Glue vs Elastic Search comparison

Cancel
You must select at least 2 products to compare!
Amazon Web Services (AWS) Logo
12,012 views|8,420 comparisons
92% willing to recommend
Elastic Logo
190 views|61 comparisons
98% willing to recommend
Comparison Buyer's Guide
Executive Summary

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.
To learn more, read our detailed AWS Glue vs. Elastic Search Report (Updated: March 2024).
768,857 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The facility to integrate with S3 and the possibility to use Jupyter Notebook inside the pipeline are the most valuable features.""Glue is a NoSQL-based data ETL tool that has some advantages over IIS and ISAs.""The solution's technical support is good. Whenever we raise a use case where we face an issue in our company, we get a response from the solution's technical team.""I also like that you can add custom libraries like JAR files and use them. So, the ability to use a fast processing engine and embed basic jobs easily are significant advantages.""The most valuable features currently are glue studio, jobs, and triggers.""I like the fact that AWS Glue works with Python scripts.""The solution integrates well with other AWS products or services.""I like its integration and ability to handle all data-related tasks."

More AWS Glue Pros →

"The solution is quite scalable and this is one of its advantages.""I like how it allows us to connect to Kafka and get this data in a document format very easily. Elasticsearch is very fast when you do text-based searches of documents. That area is very good, and the search is very good.""X-Pack provides good features, like authorization and alerts.""Logsign provides us with the capability to execute multiple queries according to our requirements. The indexing is very high, making it effective for storing and retrieving logs. The real-time analytics with Elastic benefits us due to the huge traffic volume in our organization, which reaches up to 60,000 requests per second. With logs of approximately 25 GB per day, manually analyzing traffic behavior, payloads, headers, user agents, and other details is impractical.""I have found the sort capability of Elastic very useful for allowing us to find the information we need very quickly.""The solution has good security features. I have been happy with the dashboards and interface.""The most valuable feature is the out of the box Kibana.""It provides deep visibility into your cloud and distributed applications, from microservices to serverless architectures. It quickly identifies and resolves the root causes of issues, like gaining visibility into all the cloud-based and on-prem applications."

More Elastic Search Pros →

Cons
"One area that could be improved is the ETL view. The drag-and-drop interface is not as user-friendly as some other ETL tools.""We face performance issues when using AWS Glue for data transformation and integration.""The solution’s stability could be improved.""The mapping area and the use of the data catalog from Glue could be better.""Overall, I consider the technical support to be fine, although the response time could be faster in certain cases.""I haven't looked into Glue in terms of seeking out flaws. I've not come across missing features.""On occasion, the solution's dashboard reports that a project failed due to runtime but it actually succeeded.""The setup and installation is a bit complex without advanced knowledge or training."

More AWS Glue Cons →

"Elasticsearch could improve by honoring Unix environmental variables and not relying only on those provided by Java (e.g. installing plugins over the Unix http proxy).""The reports could improve.""The solution's integration and configuration are not easy. Not many people know exactly what to do.""Improving machine learning capabilities would be beneficial.""The metadata gets stored along with indexes and isn't queryable.""Elastic Enterprise Search's tech support is good but it could be improved.""I have not been using the solution for many years to know exactly the improvements needed. However, they could simplify how the YML files have to be structured properly.""There are potential improvements based on our client feedback, like unifying the licensing cost structure."

More Elastic Search Cons →

Pricing and Cost Advice
  • "The pricing is a bit higher than other solutions like Athena and EC2. If the pricing becomes more scaled or flexible, it will be good because you have to pay 44 cents just for one DPU for an hour. If you increase DPUs to 5 or 10, the pricing gets multiplied. There are also some time limits like 0 to 10 minutes or 10 to 20 minutes. If the pricing is according to the minutes, it would be better because you have to limit your job to 10 minutes or 20 minutes."
  • "It is not expensive. AWS Glue works on the serverless architecture. We get charged for the time the server is up. For our use case, we have to use it once in a day, and it is not expensive for us."
  • "Its price is good. We pay as we go or based on the usage, which is a good thing for us because it is simple to forecast for the tool. It is good in terms of the financial planning of the company, and it is a good way to estimate the cost. It is also simple for our clients. In my opinion, it is one of the best tools in the market for ETL processes because of the fact that you pay as you use, which separates it from other big tools such as PowerCenter, Pentaho Data Integration, and Talend."
  • "Technical support is a paid service, and which subscription you have is dependent on that. You must pay one of them, and it ranges from $15,000 to $25,000 per year."
  • "This solution is affordable and there is an option to pay for the solution based on your usage."
  • "AWS Glue is quite costly, especially for small organizations."
  • "AWS Glue uses a pay-as-you-go approach which is helpful. The price of the overall solution is low and is a great advantage."
  • "The overall cost of AWS Glue could be better. It cost approximately $1,000 a month. There is paid support available from AWS Glue."
  • More AWS Glue Pricing and Cost Advice →

  • "ELK has been considered as an alternative to Splunk to reduce licensing costs."
  • "An X-Pack license is more affordable than Splunk."
  • "​The pricing and license model are clear: node-based model."
  • "This is a free, open source software (FOSS) tool, which means no cost on the front-end. There are no free lunches in this world though. Technical skill to implement and support are costly on the back-end with ELK, whether you train/hire internally or go for premium services from Elastic."
  • "We are using the free version and intend to upgrade."
  • "It can be expensive."
  • "This product is open-source and can be used free of charge."
  • "We are using the open-sourced version."
  • More Elastic Search Pricing and Cost Advice →

    report
    Use our free recommendation engine to learn which Cloud Data Integration solutions are best for your needs.
    768,857 professionals have used our research since 2012.
    Questions from the Community
    Top Answer:AWS Glue and Azure Data factory for ELT best performance cloud services.
    Top Answer:We reviewed AWS Glue before choosing Talend Open Studio. AWS Glue is the managed ETL (extract, transform, and load) from Amazon Web Services. AWS Glue enables AWS users to create and manage jobs in… more »
    Top Answer:AWS Glue's main use case is for allowing users to discover, prepare, move, and integrate data from multiple sources. The product lets you use this data for analytics, application development, or… more »
    Top Answer:Logsign provides us with the capability to execute multiple queries according to our requirements. The indexing is very high, making it effective for storing and retrieving logs. The real-time… more »
    Top Answer:I don't see improvements at the moment. The current setup is working well for me, and I'm satisfied with it. Integrating with different platforms is also fine, and I'm not recommending any changes or… more »
    Ranking
    1st
    Views
    12,012
    Comparisons
    8,420
    Reviews
    32
    Average Words per Review
    419
    Rating
    7.8
    9th
    Views
    190
    Comparisons
    61
    Reviews
    27
    Average Words per Review
    501
    Rating
    8.3
    Comparisons
    Also Known As
    Elastic Enterprise Search, Swiftype, Elastic Cloud
    Learn More
    Overview

    AWS Glue is a serverless cloud data integration tool that facilitates the discovery, preparation, movement, and integration of data from multiple sources for machine learning (ML), analytics, and application development. The solution includes additional productivity and data ops tooling for running jobs, implementing business workflows, and authoring.

    AWS Glue allows users to connect to more than 70 diverse data sources and manage data in a centralized data catalog. The solution facilitates visual creation, running, and monitoring of extract, transform, and load (ETL) pipelines to load data into users' data lakes. This Amazon product seamlessly integrates with other native applications of the brand and allows users to search and query cataloged data using Amazon EMR, Amazon Athena, and Amazon Redshift Spectrum.

    The solution also utilizes application programming interface (API) operations to transform users' data, create runtime logs, store job logic, and create notifications for monitoring job runs. The console of AWS Glue connects all of these services into a managed application, facilitating the monitoring and operational processes. The solution also performs provisioning and management of the resources required to run users' workloads in order to minimize manual work time for organizations.

    AWS Glue Features

    AWS Glue groups its features into four categories - discover, prepare, integrate, and transform. Within those groups are the following features:

    • Automatic schema discovery: AWS Glue crawlers connect to the organization's source or target data source through a prioritized list of classifiers to determine the schema for users' data. This feature creates metadata in companies' AWS Glue Data Catalog.

    • Schemas for data stream management: The AWS Glue Schema Registry enables users to validate and control the evolution of streaming data through registered Apache Avro schemas for no additional charge.

    • Automatic scaling based on workload: This feature dynamically scales resources up and down based on workload. The feature controls job resources, removing them depending on how much the workload can be split up.

    • FindMatches: This feature is for machine learning-based data deduplication and cleansing, and works by finding records that are imperfect matches of each other to remove useless data copies.

    • Edit, debug, and test ETL code: This feature helps users who have chosen to interactively develop their ETL code by providing development endpoints for editing, debugging, and testing the code it generates for them.

    • AWS Glue DataBrew: An interactive, point-and-click visual interface for specialists to clean and normalize data without the need to write any code.

    • AWS Glue Interactive Sessions: This feature simplifies the development of data integration jobs by enabling data engineers to interactively prepare and explore data.

    • AWS Glue Studio Job Notebooks: This AWS Glue feature provides serverless notebooks with minimal setup, allowing developers to start working in a timely manner.

    • Complex ETL pipeline building: This feature allows the product to be invoked on a schedule, on demand, or based on an event, allowing users to start multiple jobs in parallel or specify dependencies to build complex ETL pipelines.

    • AWS Glue Studio: This AWS Glue feature allows users to visually transform data through a drag-and-drop interface. The product automatically generates the code for ETL processes for users' data.

    AWS Glue Benefits

    AWS Glue offers a wide range of benefits for its users. These benefits include:

    • Users of other AWS products can easily onboard with AWS Glue, as it is integrated across a wide range of the company's services.

    • The solution is serverless, which allows for a lower total cost of ownership.

    • AWS Glue offers more power for users, as it automates much of the effort in building, maintaining, and running ETL jobs.

    • The product allows customers to easily discover and search across all their AWS datasets through AWS Glue Data Catalog.

    • AWS Glue does not require additional payment for managing and enforcing schemas for data streams.

    • The solution facilitates the authority of scalable ETL jobs for beginners and non-coding experts through a drag-and-drop interface.

    Reviews from Real Users

    Mustapha A., a cloud data engineer at Jems Groupe, likes AWS Glue because it is a product that is great for serverless data transformations.

    Liana I., CEO at Quark Technologies SRL, describes AWS Glue as a highly scalable, reliable, and beneficial pay-as-you-go pricing model.

    Elasticsearch is a prominent open-source search and analytics engine known for its scalability, reliability, and straightforward management. It's a favored choice among enterprises for real-time data search, analysis, and visualization. Open-source Elasticsearch is free, offering a comprehensive feature set and scalability. It allows full control over deployments but requires managing and maintaining the infrastructure. On the other hand, Elastic Cloud provides a managed service with features like automated provisioning, high availability, security, and global reach.

    Elasticsearch excels in handling time-sensitive data and complex search requirements across large datasets. Its scalability allows it to handle growing data volumes efficiently, maintaining high performance and fast response times. Integrated with Kibana, Elasticsearch enables powerful data visualization, providing real-time insights crucial for data-driven decision-making.

    Elastic Cloud reduces operational overhead and improves scalability and performance, though it comes with associated costs. It is available on your preferred cloud provider — AWS, Azure, or Google Cloud. Customers who want to manage the software themselves, whether on public, private, or hybrid cloud, can download the Elastic Stack.

    At its core, Elasticsearch is renowned for its full-text search capabilities, capable of performing complex queries and supporting features like fuzzy matching and auto-complete.

    Peer reviews from various professionals highlight its strengths and weaknesses. Pros include its detection and correlation features, flexibility, cloud-readiness, extensibility, and efficient search capabilities. However, users have noted challenges like steep learning curves, data analysis limitations, and integration complexities. The platform is generally viewed as stable and scalable, with varying degrees of satisfaction regarding its usability and feature set.

    In summary, Elasticsearch stands out for its high-speed search, scalability, and versatile analytics, making it a go-to solution for organizations managing large datasets. Its adaptability to different enterprise needs, robust community support, and continuous development keep it at the forefront of enterprise search and analytics solutions. However, potential users should be aware of its learning curve and the need for skilled personnel for optimization.

    Sample Customers
    bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday
    T-Mobile, Adobe, Booking.com, BMW, Telegraph Media Group, Cisco, Karbon, Deezer, NORBr, Labelbox, Fingerprint, Relativity, NHS Hospital, Met Office, Proximus, Go1, Mentat, Bluestone Analytics, Humanz, Hutch, Auchan, Sitecore, Linklaters, Socren, Infotrack, Pfizer, Engadget, Airbus, Grab, Vimeo, Ticketmaster, Asana, Twilio, Blizzard, Comcast, RWE and many others.
    Top Industries
    REVIEWERS
    Computer Software Company47%
    Financial Services Firm18%
    Pharma/Biotech Company12%
    Consumer Goods Company6%
    VISITORS READING REVIEWS
    Financial Services Firm19%
    Computer Software Company14%
    Manufacturing Company7%
    Insurance Company7%
    REVIEWERS
    Financial Services Firm33%
    Computer Software Company27%
    Manufacturing Company10%
    Insurance Company7%
    VISITORS READING REVIEWS
    Computer Software Company18%
    Financial Services Firm15%
    Government7%
    Manufacturing Company7%
    Company Size
    REVIEWERS
    Small Business29%
    Midsize Enterprise13%
    Large Enterprise58%
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise12%
    Large Enterprise73%
    REVIEWERS
    Small Business41%
    Midsize Enterprise11%
    Large Enterprise48%
    VISITORS READING REVIEWS
    Small Business24%
    Midsize Enterprise13%
    Large Enterprise63%
    Buyer's Guide
    AWS Glue vs. Elastic Search
    March 2024
    Find out what your peers are saying about AWS Glue vs. Elastic Search and other solutions. Updated: March 2024.
    768,857 professionals have used our research since 2012.

    AWS Glue is ranked 1st in Cloud Data Integration with 37 reviews while Elastic Search is ranked 9th 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, SSIS, Informatica Cloud Data Integration and Talend Open Studio, whereas Elastic Search is most compared with Faiss, Milvus, Azure Search, Pinecone and Amazon Kendra. See our AWS Glue vs. Elastic Search report.

    See our list of best Cloud Data Integration vendors.

    We monitor all Cloud Data Integration 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.