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  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data Tools
  5. Apache Impala vs Mule

Apache Impala vs Mule

OverviewComparisonAlternatives

Overview

Apache Impala
Apache Impala
Stacks145
Followers301
Votes18
GitHub Stars34
Forks33
Mule runtime engine
Mule runtime engine
Stacks127
Followers129
Votes8

Apache Impala vs Mule: What are the differences?

Developers describe Apache Impala as "Real-time Query for Hadoop". 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. On the other hand, Mule is detailed as "Revolutionizing the way the world connects data and applications". Its mission is to connect the world’s applications, data and devices. It makes connecting anything easy with Anypoint Platform™, the only complete integration platform for SaaS, SOA and APIs. Thousands of organizations in 60 countries, from emerging brands to Global 500 enterprises, use it to innovate faster and gain competitive advantage.

Apache Impala and Mule can be categorized as "Big Data" tools.

Some of the features offered by Apache Impala are:

  • Do BI-style Queries on Hadoop
  • Unify Your Infrastructure
  • Implement Quickly

On the other hand, Mule provides the following key features:

  • Connects data
  • Connects applications
  • Integration platform

Apache Impala is an open source tool with 2.19K GitHub stars and 825 GitHub forks. Here's a link to Apache Impala's open source repository on GitHub.

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Detailed Comparison

Apache Impala
Apache Impala
Mule runtime engine
Mule runtime engine

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.

Its mission is to connect the world’s applications, data and devices. It makes connecting anything easy with Anypoint Platform™, the only complete integration platform for SaaS, SOA and APIs. Thousands of organizations in 60 countries, from emerging brands to Global 500 enterprises, use it to innovate faster and gain competitive advantage.

Do BI-style Queries on Hadoop;Unify Your Infrastructure;Implement Quickly;Count on Enterprise-class Security;Retain Freedom from Lock-in;Expand the Hadoop User-verse
Connects data;Connects applications;Integration platform;Fast
Statistics
GitHub Stars
34
GitHub Stars
-
GitHub Forks
33
GitHub Forks
-
Stacks
145
Stacks
127
Followers
301
Followers
129
Votes
18
Votes
8
Pros & Cons
Pros
  • 11
    Super fast
  • 1
    Replication
  • 1
    Load Balancing
  • 1
    Open Sourse
  • 1
    Massively Parallel Processing
Pros
  • 4
    Open Source
  • 2
    Integration
  • 2
    Microservices
Integrations
Hadoop
Hadoop
Mode
Mode
Redash
Redash
Apache Kudu
Apache Kudu
CloudApp
CloudApp
API Umbrella
API Umbrella
Zapier
Zapier

What are some alternatives to Apache Impala, Mule runtime engine?

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.

Vertica

Vertica

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

Azure Synapse

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

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