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  1. Stackups
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  5. Hue vs Talend

Hue vs Talend

OverviewDecisionsComparisonAlternatives

Overview

Hue
Hue
Stacks55
Followers98
Votes0
Talend
Talend
Stacks297
Followers249
Votes0

Hue vs Talend: What are the differences?

Introduction: Hue and Talend are both data integration tools that offer various capabilities for managing and analyzing data. Understanding the key differences between these tools is essential for making an informed decision about which one to use for your specific data needs.

1. User Interface: Hue provides a user-friendly interface that is primarily web-based, making it easy for users to interact with Hadoop and other big data technologies. On the other hand, Talend offers a more traditional graphical user interface (GUI) for designing data integration workflows.

2. Integration Capabilities: Talend is known for its robust data integration capabilities, including tools for connecting, accessing, and transforming data from different sources. In contrast, Hue is more focused on providing a user-friendly interface for interacting with data stored in Hadoop and related technologies.

3. Open Source vs. Commercial: Hue is an open-source project developed by the Apache Software Foundation, making it freely available for anyone to download and use. Talend, on the other hand, offers both open-source and commercial versions of its software, providing additional features and support for users who require it.

4. Extensibility and Customization: Talend provides a wide range of components and connectors that users can leverage to build custom data integration workflows tailored to their specific needs. While Hue offers some customization options, it is not as extensible as Talend in terms of building complex data integration solutions.

5. Scalability and Performance: Talend is designed to handle large volumes of data and can scale to meet the needs of enterprise-level data integration projects. While Hue can also support scalability to some extent, it may not be as efficient or optimized for handling massive amounts of data as Talend.

6. Deployment Options: Talend offers flexibility in deployment options, allowing users to choose between on-premises, cloud, or hybrid deployment models. In contrast, Hue is mainly used within Hadoop ecosystems and may have more limited deployment options compared to Talend.

In Summary, Understanding the key differences between Hue and Talend in terms of user interface, integration capabilities, open-source vs. commercial models, extensibility, scalability, and deployment options is crucial for selecting the right data integration tool for your specific requirements.

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Advice on Hue, Talend

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

Hue
Hue
Talend
Talend

It is open source and lets regular users import their big data, query it, search it, visualize it and build dashboards on top of it, all from their browser.

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.

Statistics
Stacks
55
Stacks
297
Followers
98
Followers
249
Votes
0
Votes
0

What are some alternatives to Hue, Talend?

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.

Presto

Presto

Distributed SQL Query Engine for Big Data

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.

Apache Kylin

Apache Kylin

Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, originally contributed from eBay Inc.

Splunk

Splunk

It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.

Apache Impala

Apache Impala

Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.

Vertica

Vertica

It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.

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