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Cloudant VS Apache Spark

Compare Cloudant VS Apache Spark and see what are their differences

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

Cloudant logo Cloudant

A scalable JSON document database for web, mobile, IoT and serverless applications.

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.
  • Cloudant Landing page
    Landing page //
    2023-02-07
  • Apache Spark Landing page
    Landing page //
    2021-12-31

Cloudant videos

+ Add

Introduction to Cloudant

More videos:

  • Review - Why Cloudant? Database clusters, Web apps & more
  • Review - Connect IBM Cloud Cloudant with Postman

Apache Spark videos

+ Add

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 Cloudant and Apache Spark)

Cloudant

Apache Spark

Databases
20 20%
Databases
80% 80
NoSQL Databases
100 100%
NoSQL Databases
0% 0
Big Data
0 0%
Big Data
100% 100
Relational Databases
100 100%
Relational Databases
0% 0

User comments

Share your experience with using Cloudant and Apache Spark. For example, how are they different and which one is better?
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Reviews

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

Cloudant Reviews

9 Best MongoDB alternatives in 2019
IBM Cloudant is a distributed DBMS system and full management JSON document. It helps you to store web and mobile apps which allows you to maintain data access and availability at extreme scale.
Source: www.guru99.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 more popular. It has been mentiond 56 times since March 2021. 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.

Cloudant mentions (0)

We have not tracked any mentions of Cloudant yet. Tracking of Cloudant recommendations started around Mar 2021.

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 / 4 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 / 10 months ago
View more

What are some alternatives?

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

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

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

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

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

ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.

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

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