Pachyderm vs Apache Kudu | What are the differences? | StackShare

Kudu vs Pachyderm

Overview

Pachyderm

Stacks24

Followers95

Votes5

Apache Kudu

Stacks71

Followers259

Votes10

GitHub Stars828

Forks282

Kudu vs Pachyderm: What are the differences?

What is Kudu? Fast Analytics on Fast Data. A columnar storage manager developed for the Hadoop platform. A new addition to the open source Apache Hadoop ecosystem, Kudu completes Hadoop's storage layer to enable fast analytics on fast data.

What is Pachyderm? MapReduce without Hadoop. Analyze massive datasets with Docker. Pachyderm is an open source MapReduce engine that uses Docker containers for distributed computations.

Kudu and Pachyderm can be primarily classified as "Big Data" tools.

Kudu and Pachyderm are both open source tools. It seems that Pachyderm with 3.81K GitHub stars and 369 forks on GitHub has more adoption than Kudu with 789 GitHub stars and 263 GitHub forks.

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Detailed Comparison

Pachyderm	Apache Kudu
Pachyderm is an open source MapReduce engine that uses Docker containers for distributed computations.	A new addition to the open source Apache Hadoop ecosystem, Kudu completes Hadoop's storage layer to enable fast analytics on fast data.
Git-like File System;Dockerized MapReduce;Microservice Architecture;Deployed with CoreOS	-
Statistics
GitHub Stars -	GitHub Stars 828
GitHub Forks -	GitHub Forks 282
Stacks 24	Stacks 71
Followers 95	Followers 259
Votes 5	Votes 10
Pros & Cons
Pros 3 Containers 1 Can run on GCP or AWS 1 Versioning Cons 1 Recently acquired by HPE, uncertain future.	Pros 10 Realtime Analytics Cons 1 Restart time
Integrations
Docker Amazon EC2 Google Compute Engine Vagrant	Hadoop

What are some alternatives to Pachyderm, Apache Kudu?

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

Distributed SQL Query Engine for Big Data

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 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

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 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™ 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

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

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.