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

Mule vs Vespa

OverviewComparisonAlternatives

Overview

Mule runtime engine
Mule runtime engine
Stacks127
Followers129
Votes8
Vespa
Vespa
Stacks12
Followers29
Votes0
GitHub Stars6.5K
Forks675

Mule vs Vespa: What are the differences?

## Key Differences between Mule and Vespa

The Mule runtime engine, developed by MuleSoft, is an open-source messaging infrastructure and integration platform. On the other hand, Vespa is an open-source, big data processing and serving engine developed by Yahoo. One key difference between Mule and Vespa is their primary use cases. Mule is primarily used for integration and messaging purposes, enabling communication between various systems and applications. In contrast, Vespa is designed for massive data processing and serving, making it ideal for applications that require real-time, high-performance data retrieval and analysis. Another significant difference between the two is their architecture. Mule follows an integration-centric architecture, providing a platform for building connections between disparate systems using APIs and messaging protocols. In comparison, Vespa employs a distributed, cloud-native architecture that enables efficient processing and serving of large datasets across multiple nodes.

In Summary, Mule is focused on integration and messaging, while Vespa excels in big data processing and serving with its distributed architecture. 

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Detailed Comparison

Mule runtime engine
Mule runtime engine
Vespa
Vespa

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.

Vespa is an engine for low-latency computation over large data sets. It stores and indexes your data such that queries, selection and processing over the data can be performed at serving time.

Connects data;Connects applications;Integration platform;Fast
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Statistics
GitHub Stars
-
GitHub Stars
6.5K
GitHub Forks
-
GitHub Forks
675
Stacks
127
Stacks
12
Followers
129
Followers
29
Votes
8
Votes
0
Pros & Cons
Pros
  • 4
    Open Source
  • 2
    Microservices
  • 2
    Integration
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Integrations
CloudApp
CloudApp
API Umbrella
API Umbrella
Zapier
Zapier
Hadoop
Hadoop
Pig
Pig

What are some alternatives to Mule runtime engine, Vespa?

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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