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Pachyderm

20
64
+ 1
5
Vespa

10
22
+ 1
0
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Pachyderm vs Vespa: What are the differences?

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

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

Pachyderm and Vespa are both open source tools. Pachyderm with 3.81K GitHub stars and 369 forks on GitHub appears to be more popular than Vespa with 2.85K GitHub stars and 339 GitHub forks.

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Pros of Pachyderm
Pros of Vespa
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    Containers
  • 1
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  • 1
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    What is Pachyderm?

    Pachyderm is an open source MapReduce engine that uses Docker containers for distributed computations.

    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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    What companies use Pachyderm?
    What companies use Vespa?
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    What tools integrate with Pachyderm?
    What tools integrate with Vespa?

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    What are some alternatives to Pachyderm and Vespa?
    Hadoop
    The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
    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.
    Airflow
    Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
    Kafka
    Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
    DVC
    It is an open-source Version Control System for data science and machine learning projects. It is designed to handle large files, data sets, machine learning models, and metrics as well as code.
    See all alternatives