StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data Tools
  5. Matillion vs Talend

Matillion vs Talend

OverviewDecisionsComparisonAlternatives

Overview

Talend
Talend
Stacks297
Followers249
Votes0
Matillion
Matillion
Stacks51
Followers71
Votes0
GitHub Stars0
Forks0

Matillion vs Talend: What are the differences?

### **Key Differences Between Matillion and Talend**

1. **Deployment Model**: Matillion is a cloud-native ETL tool, designed specifically for cloud-based data warehouses like Snowflake, Amazon Redshift, and Google BigQuery. Talend, on the other hand, offers both on-premise and cloud-based solutions, providing users with more flexibility in choosing their deployment model.

2. **User Interface**: Matillion boasts a user-friendly drag-and-drop interface that facilitates rapid development and deployment of data pipelines. In contrast, Talend requires more coding and configuration, making it better suited for users with a deeper technical background.

3. **Scalability**: Matillion is known for its scalability, allowing organizations to seamlessly adapt to changing data volumes and processing needs without compromising performance. Talend also offers scalability but may require additional configuration and optimization for large-scale data processing.

4. **Plugin Ecosystem**: Talend offers a wide range of plugins and connectors that enhance its integration capabilities, enabling users to connect with various data sources and systems. While Matillion has a growing ecosystem of plugins, it may not have the same breadth as Talend in terms of third-party integrations.

5. **Cost Structure**: Matillion typically follows a subscription-based pricing model, where users pay based on their usage and the number of users. Talend offers different pricing tiers, including a free open-source option, making it more accessible to users with budget constraints.

6. **Community Support**: Talend has a larger community of users and developers, which can be beneficial in terms of finding resources, tutorials, and troubleshooting tips. Matillion's community support may be more limited, as it is a newer player in the market.

In Summary, Matillion and Talend differ in their deployment model, user interface, scalability, plugin ecosystem, cost structure, and community support.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Advice on Talend, Matillion

karunakaran
karunakaran

Consultant

Jun 26, 2020

Needs advice

I am trying to build a data lake by pulling data from multiple data sources ( custom-built tools, excel files, CSV files, etc) and use the data lake to generate dashboards.

My question is which is the best tool to do the following:

  1. Create pipelines to ingest the data from multiple sources into the data lake
  2. Help me in aggregating and filtering data available in the data lake.
  3. Create new reports by combining different data elements from the data lake.

I need to use only open-source tools for this activity.

I appreciate your valuable inputs and suggestions. Thanks in Advance.

80.4k views80.4k
Comments

Detailed Comparison

Talend
Talend
Matillion
Matillion

It is an open source software integration platform helps you in effortlessly turning data into business insights. It uses native code generation that lets you run your data pipelines seamlessly across all cloud providers and get optimized performance on all platforms.

It is a modern, browser-based UI, with powerful, push-down ETL/ELT functionality. With a fast setup, you are up and running in minutes.

-
Edit, Transform and Load Data intuitively; Load Data from Dozens of Sources; 50% reduction in ETL development and maintenance effort ; Rich orchestration environment; Work as a team; Cheap; Billing via AWS.
Statistics
GitHub Stars
-
GitHub Stars
0
GitHub Forks
-
GitHub Forks
0
Stacks
297
Stacks
51
Followers
249
Followers
71
Votes
0
Votes
0
Integrations
No integrations available
Amazon S3
Amazon S3
Zendesk
Zendesk
MongoDB Stitch
MongoDB Stitch
Amazon Redshift
Amazon Redshift
Cassandra
Cassandra
Salesforce Sales Cloud
Salesforce Sales Cloud
Mixpanel
Mixpanel

What are some alternatives to Talend, Matillion?

Google BigQuery

Google BigQuery

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

Apache Spark

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Amazon Redshift

Amazon Redshift

It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.

Qubole

Qubole

Qubole is a cloud based service that makes big data easy for analysts and data engineers.

Presto

Presto

Distributed SQL Query Engine for Big Data

Amazon EMR

Amazon EMR

It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.

Amazon Athena

Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

Apache Flink

Apache Flink

Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.

lakeFS

lakeFS

It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.

Druid

Druid

Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

Related Comparisons

Bootstrap
Materialize

Bootstrap vs Materialize

Laravel
Django

Django vs Laravel vs Node.js

Bootstrap
Foundation

Bootstrap vs Foundation vs Material UI

Node.js
Spring Boot

Node.js vs Spring-Boot

Liquibase
Flyway

Flyway vs Liquibase