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  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data Tools
  5. Pig vs Zato

Pig vs Zato

OverviewComparisonAlternatives

Overview

Pig
Pig
Stacks57
Followers111
Votes5
GitHub Stars686
Forks447
Zato
Zato
Stacks12
Followers24
Votes0
GitHub Stars988
Forks246

Pig vs Zato: What are the differences?

What is Pig? Platform for analyzing large data sets. Pig is a dataflow programming environment for processing very large files. Pig's language is called Pig Latin. A Pig Latin program consists of a directed acyclic graph where each node represents an operation that transforms data Operations are of two flavors: (1) relational-algebra style operations such as join, filter, project; (2) functional-programming style operators such as map, reduce. .

What is Zato? Open-source ESB, SOA, REST and Cloud Integrations in Python. Build and orchestrate integration services, expose new or existing APIs, either cloud or on-premise, and use a wide range of connectors, data formats and protocols.

Pig and Zato can be primarily classified as "Big Data" tools.

Pig and Zato are both open source tools. It seems that Zato with 783 GitHub stars and 185 forks on GitHub has more adoption than Pig with 581 GitHub stars and 449 GitHub forks.

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Detailed Comparison

Pig
Pig
Zato
Zato

Pig is a dataflow programming environment for processing very large files. Pig's language is called Pig Latin. A Pig Latin program consists of a directed acyclic graph where each node represents an operation that transforms data. Operations are of two flavors: (1) relational-algebra style operations such as join, filter, project; (2) functional-programming style operators such as map, reduce.

Connect, integrate and automate all of your systems, APIs and apps, including cloud and legacy ones, using an open-source integration platform in Python. ESB, SOA, REST, API and Cloud Integrations in Python.

-
Integrate everything. In Python.; Connect, integrate and automate all of your systems, APIs and apps, including cloud and legacy ones, using an open-source integration platform in Python.;Say goodbye to integration challenges and hello to peace of mind.
Statistics
GitHub Stars
686
GitHub Stars
988
GitHub Forks
447
GitHub Forks
246
Stacks
57
Stacks
12
Followers
111
Followers
24
Votes
5
Votes
0
Pros & Cons
Pros
  • 2
    Finer-grained control on parallelization
  • 1
    Open-source
  • 1
    Join optimizations for highly skewed data
  • 1
    Proven at Petabyte scale
No community feedback yet
Integrations
No integrations available
Docker
Docker
MySQL
MySQL
Linux
Linux
MSSQL
MSSQL
Microsoft Azure
Microsoft Azure
Amazon S3
Amazon S3
PostgreSQL
PostgreSQL
Odoo
Odoo
Ubuntu
Ubuntu
SQL
SQL

What are some alternatives to Pig, Zato?

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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