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Pig

Stacks37

Followers50

+ 1

Votes4

Vespa

Stacks4

Followers12

+ 1

Votes0

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Pig vs Vespa: What are the differences?

Developers describe Pig as "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. . On the other hand, Vespa is detailed as "Store, search, rank and organize big data". 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.

Pig and Vespa belong to "Big Data Tools" category of the tech stack.

Pig and Vespa are both open source tools. Vespa with 2.85K GitHub stars and 339 forks on GitHub appears to be more popular than Pig with 583 GitHub stars and 449 GitHub forks.

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What is Pig?

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 Vespa?

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.

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Why do developers choose Pig?

Why do developers choose Vespa?

1
Open-source
1
Proven at Petabyte scale
1
Join optimizations for highly skewed data
1
Finer-grained control on parallelization

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Jobs that mention Pig and Vespa as a desired skillset

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What tools integrate with Pig?

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What are some alternatives to Pig and Vespa?

Capybara

Capybara helps you test web applications by simulating how a real user would interact with your app. It is agnostic about the driver running your tests and comes with Rack::Test and Selenium support built in. WebKit is supported through an external gem.

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.

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.

Presto

Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes.

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