Tools To Manage Big Data

If you operate a large organization, then there’s no doubt you deal with a massive amount of data every day. We used to talk about manipulating gigabytes of raw data, but now even individual users at home are dealing with terabytes. Big data means that companies need ways to search, analyze, and use petabytes of data in reasonable amounts of time. If you don’t have software solutions to help you deal with large volumes of data, you’ll have a difficult time making informed business decisions, developing new products, and helping your customers. Here are just a few great options you have for big data software.


While most users will be fine with using a popular search engine like Google or Bing, your business needs a search solution that can quickly index all your data from potentially millions of web pages and make it searchable in real-time under conditions of any kind. Elasticsearch is an open-source, full-text search and analytics engine. It’s built on the Apache Lucene project and is the main component of the Elastic Stack, which also includes LogStash and Kibana.

Elasticsearch uses LogStash to simultaneously pull from multiple data sources and organize the data in Elasticsearch indexes via a process known as data ingestion. These indices are stored on server nodes, and each Elasticsearch index is made up of shards of relevant data. Each primary shard is backed up by replica shards to ensure data is always available. All data is stored in the form of JSON documents. Thanks to the inverted index structure, which scans all documents for each unique word and for how many times each word appears in each document, relevant results for Elasticsearch queries can be returned almost immediately once data is indexed.

Elasticsearch is compatible with all operating systems, and it works with many popular programming languages including Python, JavaScript, and Ruby. The Elasticsearch service can be deployed physically on your own hardware, though this requires you to install each component of the ELK Stack individually. Using the Elastic Cloud is easier, and it also ensures you’re automatically updated to the latest Elasticsearch version, so you can be confident in your data security.


If you need to create professional-grade visualizations for large volumes of data but lack coding or design experience, then Datawrapper was made with you in mind. This open-source platform is frequently used by major newsrooms, and it’s used by teams including The New York TimesFortune, and Wired. It’s a fast and interactive visualization solution that boasts compatibility on any kind of device.

Using the platform is simple. You just need to copy and paste your data from the internet or a spreadsheet, select the type of chart or graph you want, and then customize it with colors and annotations. All that’s left is to export your new visual. Datawrapper offers a free version, although large organizations will likely want to opt for the enterprise package to support more users and take advantage of greater customization options.

Apache Hadoop

Hadoop is one of the most commonly used big data tools and has been adopted by many big names including AWS, Facebook, Intel, Microsoft, and many more. It’s essentially a framework meant to help process large sets of data across multiple computer systems while using simple programming.

Hadoop is designed with incredible scalability that can support single servers up into the thousands. Likely its greatest strength is the Hadoop Distributed File System, which allows users to hold all kinds of data (plain text, image, video, XML, JSON, etc.) in a single file system. Hadoop is written in Java and is supported across most systems, and best of all, it’s free to use under the Apache License.

(Excerpt) Read more Here | 2020-10-24 02:53:43
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