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AWS Glue VS mlsql

Compare AWS Glue VS mlsql and see what are their differences

AWS Glue

Fully managed extract, transform, and load (ETL) service

Rating
0 reviews
Alternatives Is it good?
mlsql

Infer SQL queries from plain-text questions and table headers.

Rating
0 reviews
Alternatives Is it good?
Cyclr
Powerful SaaS integration toolkit for SaaS developers - create, amplify, manage and publish native integrations from within your app with Cyclr's flexible Embedded iPaaS. sponsored
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Which is more popular?

Based on our record, AWS Glue should be more popular than mlsql. It has been mentioned 16 times since March 2021.

social mentions
16 vs 2
Data Integration popularity
100% vs 0%
alternatives listed
137 vs 1

Base details

Website, pricing, platforms and company facts side by side.

AWS Glue
mlsql
Website aws.amazon.com github.com
Listed in
Data Integration ETL Data Workflow Data Pipelines +1
Education LMS Online Learning Web App +1

Features and specs

What each product offers, as listed by its team.

AWS Glue 6 features
mlsql 0 features
  • Fully Managed
    AWS Glue is a fully managed ETL (Extract, Transform, Load) service, which means you don't need to manage any underlying infrastructure. This reduces the operational overhead and allows you to focus on the data processing tasks.
  • Scalability
    AWS Glue can automatically scale resources up or down based on the demand and workload, ensuring optimal performance without manual intervention.
  • Serverless
    Being serverless, there are no servers to manage or maintain. You only pay for the resources that you consume, which can result in significant cost savings.
  • Integrated Data Catalog
    AWS Glue comes with a built-in data catalog that helps you organize and discover your data. It automatically indexes and maintains metadata about your data, making it easier to manage.
  • Support for Multiple Data Sources
    AWS Glue supports a variety of data sources including Amazon S3, RDS, Redshift, and many external databases, providing flexibility in your ETL processes.
  • Developer Tools
    AWS Glue provides developer endpoints for custom ETL logic, and integrates with AWS SDKs, Boto3, and the AWS CLI, allowing for a flexible development experience.

Possible disadvantages

  • Complex Pricing
    The pricing model for AWS Glue can be complicated, involving multiple components such as Data Processing Units (DPUs), data catalog storage, and crawler costs, which may make it hard to estimate costs.
  • Learning Curve
    There is a significant learning curve for developers who are new to AWS Glue, especially when it comes to understanding its various components and configurations.
  • Performance for Small Datasets
    AWS Glue is optimized for large-scale data processing, which may result in suboptimal performance and higher costs for smaller datasets.
  • Vendor Lock-in
    Using AWS Glue ties you to the AWS ecosystem, making it harder to switch to another cloud provider without significant rework of your ETL pipelines and data catalog.
  • Limited Debugging Tools
    The debugging and troubleshooting tools for AWS Glue are somewhat limited compared to other mature ETL tools, which may complicate the development and maintenance of ETL jobs.
  • Job Run Delays
    There can be delays in job startup times, which can be problematic for certain time-sensitive applications requiring near real-time data processing.

No features have been listed yet.

Analysis

An editorial look at what each product does well and who it suits.

AWS Glue
mlsql

Overall verdict

  • AWS Glue is generally considered a good option for organizations looking for a powerful, scalable, and cost-effective ETL solution within the AWS ecosystem. Its ease of integration with AWS services, managed nature, and capability to handle large volumes of data make it a strong choice, particularly for teams that are already using AWS services.

Why this product is good

  • AWS Glue is a fully managed ETL (Extract, Transform, Load) service that makes it easy to prepare and transform data for analytics, machine learning, and application development. It is particularly beneficial for its serverless architecture, which allows users to run data processing jobs without the need to manage any infrastructure. The service integrates seamlessly with other AWS services like S3, RDS, and Redshift, providing a robust ecosystem for data processing. It also supports a wide range of data sources and formats, and offers a graphical interface for easy job creation and monitoring.

Recommended for

  • Organizations already using AWS services and looking to streamline their ETL processes.
  • Data engineers and developers who need a scalable solution to handle large datasets without managing infrastructure.
  • Companies that require seamless integration with a wide array of data storage options and formats.

Overall verdict

  • MLSQL is a solid open-source unified platform that blends SQL with machine learning, making data engineering and ML workflows accessible through a single, declarative language. It's a good choice for teams looking to streamline big data and ML pipelines without switching between multiple tools.

Why this product is good

  • It unifies data processing and machine learning under a single SQL-like syntax, lowering the learning curve for data teams.
  • Built on top of Apache Spark, it leverages a proven distributed computing engine for handling large-scale data.
  • Open-source and actively developed, allowing customization and community-driven improvements.
  • Supports the full ML lifecycle including data preprocessing, training, and deployment within one workflow.
  • Reduces the need to context-switch between separate ETL, analytics, and ML tools.

Recommended for

  • Data engineers and data scientists who prefer SQL-centric workflows
  • Teams working with big data on Apache Spark
  • Organizations wanting to unify ETL and machine learning pipelines
  • Companies seeking an open-source alternative to fragmented ML tooling
  • Analysts looking to build ML models without deep programming expertise

Videos

Walkthroughs and reviews on video.

AWS Glue 4 videos + Add
mlsql 0 videos + Add

Build ETL Processes for Data Lakes with AWS Glue - AWS Online Tech Talks

More videos

  • - AWS re:Invent BDT 201: AWS Data Pipeline: A guided tour
  • - Getting Started with AWS Glue Data Catalog
  • - Bajaj Housing Finance Limited: Serverless Data Pipelines with AWS Glue and Amazon Aurora PGSQL

No mlsql videos yet. You could help us improve this page by suggesting one.

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
AWS Glue
mlsql
100% 100%
Data Integration
0% 0%
0% 0%
LMS
100% 100%
100% 100%
ETL
0% 0%
0% 0%
Education
100% 100%

User comments

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Reviews and articles

External articles and on-site reviews we used to compare the two products.

AWS Glue no reviews yet
mlsql no reviews yet
  • Best ETL Tools: A Curated List
    estuary.dev · Apr 2025

    AWS Glue is a fully managed serverless ETL service from Amazon Web Services (AWS) designed to automate and simplify the data preparation process for analytics. Its serverless architecture eliminates the need to manage...

  • 10 Best ETL Tools (October 2023)
    www.unite.ai · Oct 2023

    AWS Glue is an end-to-end ETL offering intended to make ETL workloads easier and more integratable with the larger AWS ecosystem. One of the more unique aspects of the tool is that it is serverless, meaning Amazon...

  • 15+ Best Cloud ETL Tools
    estuary.dev · Sep 2023

    AWS Glue is a serverless data integration service designed to streamline analytics, machine learning, and app development tasks. It discovers, prepares, and moves data from a myriad of sources and offers a seamless...

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Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

AWS Glue 16 mentions
mlsql 2 mentions

View more

  • Download the files from Docker Container and locally edit them
    I am working on a project that requires me to take user input (as English) and return SQL queries. We will eventually be working with multiple datasets, which is why the valuenet over at https://github.com/paulfitz/mlsql ended up being... Source: over 4 years ago
  • Clone and edit Docker Projects hosted on Github
    I found this great resource here: https://github.com/paulfitz/mlsql. Source: almost 5 years ago

Alternatives to AWS Glue and mlsql

When comparing AWS Glue and mlsql, you can also consider the following products.

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