What is better Apache Spark or DataMelt? We are here to improve the process of comparing Data Analytics Software products for you. For example, on this page you can look at the overall performance of Apache Spark (9.8) and compare it with the overall performance of DataMelt (8.0). You can also match their overall user satisfaction rating: Apache Spark (97%) vs. DataMelt (98%).
What’s more, you can read their functions carefully to check which product can better address your company’s requirements. In general, any business solution must let you to immediately view the big picture, all the while allowing you quick access to the details.
If you want to quickly find the more reliable Data Analytics Software according to our review team we suggest you examine these services: IBM Business Analytics, Apache Hadoop, Apache Spark.
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.
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.
Almost as important as useful features and user support level are pricing packages made available by Apache Spark and DataMelt. While price should not be the only element it’s definitely a key thing to consider. You should try to find a flexible pricing package that can be adjusted to your team size and easily scaled up every time your team develops. Make sure you don’t select packages that have complex functionalities that you won’t find useful and always make an effort to contact with the vendor directly as big companies can often count on discounts. You should also give a chance to a free trial or demo of every product to spend at least some time working with it. It’s a valuable experience that doesn’t ask you to invest any money and provides you with a practical overview of what it feels like to work with Apache Spark and DataMelt.
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