Matillion Data Productivity Cloud and AWS Glue compete in the data integration and ETL category, with Matillion holding an edge in ease of setup and integration capabilities, while AWS Glue stands out for scalability and integration with AWS services.
Features: Matillion is praised for its ease of setup and broad integration capabilities, especially efficient with Salesforce, significantly reducing setup time. It offers an intuitive design and strong integration with AWS services. AWS Glue excels in scalability and seamless AWS integration, offering a valuable data catalog and serverless processing features. It also provides robust real-time data processing and automation capabilities.
Room for Improvement: Matillion could improve with more frequent updates to align with API changes, enhanced documentation, and better connectivity with diverse data sources. Optimization of performance and efficiency is also suggested. AWS Glue faces challenges due to AWS exclusivity, complex initial configurations, and high-cost scaling. Users note its performance can suffer from complex setups and inadequate documentation.
Ease of Deployment and Customer Service: Both Matillion and AWS Glue provide versatile deployment options across cloud environments. Matillion is recognized for its responsive customer service, knowledgeable support, and comprehensive documentation. AWS Glue fares well in customer service, but users indicate room for improvement in technical documentation to enhance satisfaction.
Pricing and ROI: Matillion offers a consistent pricing model across team sizes, being perceived as cost-effective, though somewhat expensive by some. Users highlight quick ROI. AWS Glue’s pay-as-you-go model is seen as costly, especially as usage scales, but justifiable given its advanced features. Both solutions help in minimizing operational costs and achieving ROI, with pricing remaining a key consideration.
I advocate using Glue in such cases.
Consequently, we adjusted our processes to use Matillion Data Productivity Cloud only for extraction and ingestion, while Snowflake handled all transformations and jobs.
For complex Glue-related problems such as job failures or permission issues, their documentation is good, but having direct access to support helps cut down troubleshooting time significantly.
AWS's documentation is reliable, and careful reference often resolves missed upgrade details.
They communicate effectively and respond quickly to all inquiries.
It is beneficial to upgrade jobs, and we conduct extensive testing in development before migrating to production.
It can easily handle data from one terabyte to 100 terabytes or more, scaling nicely with larger datasets.
Depending on the nature of data sets, volume, and mixture of different data, the scalability could be improved as manual code writing is still required.
The autoscale process works well, allowing the system to start another node automatically if the first machine reaches 80% capacity.
As a managed service, it reduces management burdens.
Learning the latest functionalities is crucial, and while challenging, it is a vital part of staying current and ensuring an efficient ETL process.
With AWS, I gather data from multiple sources, clean it up, normalize it, de-duplicate it, and make it presentable.
A more user-friendly and simpler process would help speed up the deployment process.
The main areas for improvement are AI features and scalability.
Connections to BigQuery for extracting information are complex.
AWS charges based on runtime, which can be quite pricey.
Costing depends on resource usage, and cost optimization may involve redesigning jobs for flexibility.
Regarding AWS Glue's pricing, it is not more expensive; rather, it is very reasonable, but it is not cheap.
Matillion Data Productivity Cloud offers discounts and special deals, especially when dealing with high-volume clients or fewer existing clients in specific regions, like Spain.
The pricing is moderate, neither expensive nor cheap.
AWS Glue has reduced efforts by 60%, which is the main benefit.
AWS Glue also enhances job scheduling and orchestration capabilities, integrating with AWS Glue Studio for comprehensive data workflow management.
For ETL, I feel the performance is excellent. If I create jobs in a standard way, the performance is great, and maintenance is also seamless.
The predefined connectors eliminate the need to write code for connectivity.
Matillion Data Productivity Cloud is effective for ingest functions, particularly when moving information to Snowflake and performing many transformations.
| Product | Market Share (%) |
|---|---|
| AWS Glue | 14.4% |
| Matillion Data Productivity Cloud | 5.1% |
| Other | 80.5% |
| Company Size | Count |
|---|---|
| Small Business | 11 |
| Midsize Enterprise | 6 |
| Large Enterprise | 32 |
| Company Size | Count |
|---|---|
| Small Business | 6 |
| Midsize Enterprise | 10 |
| Large Enterprise | 11 |
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:
AWS Glue Benefits
AWS Glue offers a wide range of benefits for its users. These benefits include:
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.
Matillion Data Productivity Cloud features an intuitive graphical interface, seamless AWS integration, and efficient data management. Its tools streamline complex tasks for SFDC, RDS, Marketo, Facebook, and Google AdWords.
Matillion Data Productivity Cloud provides fast transformations with built-in verification, easy scheduling, and sampling. With automatic scalability and diverse data source support, it simplifies complex data tasks. Users benefit from cloud data warehousing and integrating data into Snowflake while appreciating its ease of use by non-technical teams. Enhancements can focus on frequent API adjustments, improved documentation, faster performance with less latency, and better error handling.
What are the key features of Matillion Data Productivity Cloud?
What benefits and ROI should users seek in reviews?
In industries such as technology, finance, and healthcare, Matillion Data Productivity Cloud is implemented to streamline ETL processes, optimize data pipeline construction, and enhance data migration efforts. It supports efficient data loading and integration between cloud and on-premises databases, aiding industries in managing data-driven projects.
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