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Upsolver VS Apache Spark

Compare Upsolver VS Apache Spark and see what are their differences

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  2. » Videos
  3. » Reviews
  4. » Alternatives

Upsolver logo Upsolver

Upsolver is a robust Data Lake Platform that simplifies big & streaming data integration, management and preparation on premise (HDFS) or in the cloud (AWS, Azure, GCP).

Apache Spark logo Apache Spark

Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
  • Upsolver Landing page
    Landing page //
    2023-08-06
  • Apache Spark Landing page
    Landing page //
    2021-12-31

Upsolver videos

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Apache Spark videos

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Weekly Apache Spark live Code Review -- look at StringIndexer multi-col (Scala) & Python testing

More videos:

  • Review - What's New in Apache Spark 3.0.0
  • Review - Apache Spark for Data Engineering and Analysis - Overview

Category Popularity

0-100% (relative to Upsolver and Apache Spark)

Upsolver

Apache Spark

Business & Commerce
100 100%
Business & Commerce
0% 0
Databases
0 0%
Databases
100% 100
Online Services
100 100%
Online Services
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Upsolver and Apache Spark

Upsolver Reviews

Top 10 AWS ETL Tools and How to Choose the Best One | Visual Flow
In this way, Upsolver removes the complexity of Big Data and Real-Time projects and reduces their use time from several weeks or months to several hours. With the latest Volcano technology, this tool queries the entire data lake in less than a millisecond and stores 10x the amount of data in RAM.
Source: visual-flow.com

Apache Spark Reviews

15 data science tools to consider using in 2021
Apache Spark is an open source data processing and analytics engine that can handle large amounts of data -- upward of several petabytes, according to proponents. Spark's ability to rapidly process data has fueled significant growth in the use of the platform since it was created in 2009, helping to make the Spark project one of the largest open source communities among big...
Source: searchbusinessanalytics.techtarget.com
Top 15 Kafka Alternatives Popular In 2021
Apache Spark is a well-known, general-purpose, open-source analytics engine for large-scale, core data processing. It is known for its high-performance quality for data processing – batch and streaming with the help of its DAG scheduler, query optimizer, and engine. Data streams are processed in real-time and hence it is quite fast and efficient. Its machine learning...
Source: www.spec-india.com
5 Best-Performing Tools that Build Real-Time Data Pipeline
Apache Spark is an open-source and flexible in-memory framework which serves as an alternative to map-reduce for handling batch, real-time analytics and data processing workloads. It provides native bindings for the Java, Scala, Python, and R programming languages, and supports SQL, streaming data, machine learning and graph processing. From its beginning in the AMPLab at...
Source: www.analyticsinsight.net

Social recommendations and mentions

Based on our record, Apache Spark seems to be a lot more popular than Upsolver. While we know about 56 links to Apache Spark, we've tracked only 1 mention of Upsolver. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Upsolver mentions (1)

  • Anyone Used Dremio?
    Most of the pains of using query engines over object storage are in the ongoing management of files (partitioning, compression, merging many small files into fewer larger files) Cloud data lakes are tremendously valuable when it comes to exploratory and ad-hoc data analysis. If you really require sub-second queries on structured data, you're better off with a data warehouse. I'm not totally clear on your use... Source: over 2 years ago

Apache Spark mentions (56)

  • Groovy 🎷 Cheat Sheet - 01 Say "Hello" from Groovy
    Recently I had to revisit the "JVM languages universe" again. Yes, language(s), plural! Java isn't the only language that uses the JVM. I previously used Scala, which is a JVM language, to use Apache Spark for Data Engineering workloads, but this is for another post 😉. - Source: dev.to / about 2 months ago
  • 🦿🛴Smarcity garbage reporting automation w/ ollama
    Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system. - Source: dev.to / 3 months ago
  • Go concurrency simplified. Part 4: Post office as a data pipeline
    Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 4 months ago
  • Five Apache projects you probably didn't know about
    Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 5 months ago
  • Spark – A micro framework for creating web applications in Kotlin and Java
    A JVM based framework named "Spark", when https://spark.apache.org exists? - Source: Hacker News / 11 months ago
View more

What are some alternatives?

When comparing Upsolver and Apache Spark, you can also consider the following products

IRI Voracity - IRI Voracity is an automated data management platform that helps you extract, transform and load (ETL) your data lake to any data warehouse or cloud.

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

Lyftrondata - Lyftrondata is an end-to-end data delivery platform, providing the right digital transformation having rapid automation and optimizations in place, so one can do better management of their inventory.

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

Mozart Data - The easiest way for teams to build a Modern Data Stack

Hadoop - Open-source software for reliable, scalable, distributed computing

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