Presto vs Apache Spark vs Talend

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Presto

394
1K
+ 1
66
Apache Spark

3K
3.5K
+ 1
140
Talend

152
248
+ 1
0
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Pros of Presto
Pros of Apache Spark
Pros of Talend
  • 18
    Works directly on files in s3 (no ETL)
  • 13
    Open-source
  • 12
    Join multiple databases
  • 10
    Scalable
  • 7
    Gets ready in minutes
  • 6
    MPP
  • 61
    Open-source
  • 48
    Fast and Flexible
  • 8
    One platform for every big data problem
  • 8
    Great for distributed SQL like applications
  • 6
    Easy to install and to use
  • 3
    Works well for most Datascience usecases
  • 2
    Interactive Query
  • 2
    Machine learning libratimery, Streaming in real
  • 2
    In memory Computation
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    Cons of Presto
    Cons of Apache Spark
    Cons of Talend
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      • 4
        Speed
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        What is Presto?

        Distributed SQL Query Engine for Big Data

        What is 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.

        What is Talend?

        It is an open source software integration platform helps you in effortlessly turning data into business insights. It uses native code generation that lets you run your data pipelines seamlessly across all cloud providers and get optimized performance on all platforms.

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        What companies use Presto?
        What companies use Apache Spark?
        What companies use Talend?

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        What tools integrate with Presto?
        What tools integrate with Apache Spark?
        What tools integrate with Talend?

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        Blog Posts

        Mar 24 2021 at 12:57PM

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        Aug 28 2019 at 3:10AM

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        PythonJavaAmazon S3+16
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        What are some alternatives to Presto, Apache Spark, and Talend?
        Stan
        A state-of-the-art platform for statistical modeling and high-performance statistical computation. Used for statistical modeling, data analysis, and prediction in the social, biological, and physical sciences, engineering, and business.
        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.
        Snowflake
        Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.
        Apache Drill
        Apache Drill is a distributed MPP query layer that supports SQL and alternative query languages against NoSQL and Hadoop data storage systems. It was inspired in part by Google's Dremel.
        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.
        See all alternatives