What is better DataMelt or Apache Spark? When choosing the best Data Analytics Software for your business our recommendation is that you compare the functions, rates, along with other crucial details concerning the product and vendor. Here, you can examine the similarities and distinctions between DataMelt (overall score at 8.0 and user satisfaction at 98%) and Apache Spark (overall score at 9.8 and user satisfaction at 97%).
You may also examine their specific modules, for example functions, plans, costs, terms, etc. Moreover, analyze the terms closely for information on extra charges, like, setup fees, separate support plan, upgrade fees, storage fees, and other similar charges.
Our experts made sure to prepare reviews of all popular Data Analytics Software products that you can find out there, but among all the ones we reviewed these three caught our special attention: IBM Business Analytics, Apache Spark, Apache Hadoop.
DataMelt is a free and open-source software environment. This means you can use it for free without worrying about any enterprise pricing plan fees.
Meanwhile, if you’re going to use the software environment for commercial purposes, you need to pay for a one-time membership fee of $20 and abide by the restrictions and conditions specified under the Creative-Commons License.
Once you become a member of the DataMelt project, you can get a commercial usage license as well as access DataMelt’s full documentation, source code and script repositories, help system, and other important files and resources.
Apache Spark is delivered based on the Apache License, a free and liberal software license that allows you to use, modify, and share any Apache software product for personal, research, commercial, or open source development purposes for free. Thus, you can use Apache Spark with no enterprise pricing plan to worry about.
Apache Spark integrates with some open source projects developed by The Apache Software Foundation as well as with third-party systems such as the following:
Apache Hadoop
Apache Mesos
HDFS (Hadoop Distributed File System)
Apache Cassandara
Apache HBase
Apache Hive
Hadoop YARN
Kubernetes
EC2
Languages Supported
English
Chinese
German
Hindi
Japanese
Spanish
French
Russian
Italian
Dutch
Portugese
Polish
Turkish
Swedish
Arabic
Prominent Clients
Anson Abraham, Data Czar, Envisagenics, Inc; Kartik Chavan, Data Analyst, The University of Texas at Arlington; Sunil Dhage, Big Data Analyst, PSL Group
Available Devices
Windows
Linux
Android
iPhone/iPad
Mac
Web-based
Windows Mobile
Company Size
Small Business
Large Enterprises
Medium Business
Freelancers
Available Support
email
phone
live support
training
tickets
General Info
An easy-to-use, lightning-fast, and unified analytics software solution developed to handle computational processes and tasks on high volumes of data, process SQL queries for structured data, streamline the creation of scalable and fault-tolerant applications that execute live stream data processing, and implement graph analytics and computation in a flexible and fast manner.
Every time you compare various Data Analytics Software software you shouldn’t just explore their list of features and provided pricing packages. Pay attention to the fact that the solution should be meeting your needs and business so the more flexible their offer the better. Check what platforms are supported by DataMelt and Apache Spark and ensure you will get mobile support for whatever devices you work on in your company. It may also be a good idea to examine which languages and countries are supported, because this may be a deal breaker for many firms.
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