Big Data Technologies 

The term "Big Data" refers to a large collection of structured and unstructured data, which continues to grow with increased digitization.

What is Big Data Technology?

Big Data has gained popularity over the years. Big data refers to the large volume, velocity, and variety of information assets that require cost-effective, innovative data processing methods for improved insight and decision-making over traditional data processing methods. 

  • As a result, businesses are adopting big data technologies to gain more insights and make more profitable decisions. 

  • Big data technologies are software applications primarily aimed at analyzing, processing, and extracting information from large datasets with highly complex structures that cannot be handled by traditional data processing technologies.



RainStor is a database management system developed by RainStor to manage and analyze big data. De-duplication is a technique that helps to store large amounts of data for reference. It eliminates duplicate files due to its ability to sort and store large amounts of information for reference.


Key features of RainStor include:


  • With RainStor large organizations can manage and analyze big data at a very low total cost.

  • The enterprise database is built on Hadoop to support fast analytics.

  • It allows you to run faster queries and analyses using SQL queries and MapReduce, resulting in 10-100x faster results.

  • RainStor offers the highest level of compression. Compared to raw data, data is compressed 40x (97.5 percent) or more and does not require re-inflation during access.



Presto is an open-source SQL query engine developed by Facebook that enables interactive query analytics on large volumes of data. This distributed search engine allows rapid analytical queries on data sources ranging from gigabytes to petabytes. This technology allows us to listen to data in place, without moving it to a separate analysis system.

Key features include:


  • Presto allows you to query data stored in Cassandra, Hive, relational databases, or proprietary data stores.

  • Presto allows you to query multiple data sources simultaneously. It allows you to use data from multiple databases in a single query.

  • It does not use MapReduce techniques and is capable of retrieving data in seconds to minutes. Query responses are usually returned within seconds.

  • Presto is easy to use because it supports standard ANSI SQL. Whether you're a developer or a data analyst, the ability to listen to your data without learning a specific language is always a plus. It easily connects to the most common BI (Business Intelligence) tools via JDBC connectors.




RapidMiner is an advanced open-source predictive analytics data mining tool. A powerful data science platform that helps data scientists and big data analysts quickly analyze their data. It supports model deployment and model operation in addition to data mining. With this solution, you get access to all the machine learning and data preparation capabilities you need to impact your business operations.

Key features include:


  • There is an integrated platform for data processing, machine learning model development, and deployment.

  • It integrates the Hadoop framework with its own RapidMiner Radoop.

  • RapidMiner Studio allows you to access, load, and analyze any type of structured or unstructured data such as text, images, and media.

  • RapidMiner supports automated predictive modeling.



ElasticSearch, based on Apache Lucene, is an open-source, distributed, modern search and analysis engine that allows you to search, index, and analyze all types of data. Log analytics, security intelligence, operational intelligence, full-text search, and business analytics are some of its common use cases. Unstructured data is obtained from various sources and stored in a format most suitable for language-based searches.


Key characteristics include:


  • You can store and analyze structured and unstructured data up to petabytes using ElasticSearch.

  • Elasticsearch simplifies data search, indexing, and querying by providing simple RESTful APIs and schema-free JSON documents.

  • Furthermore, it supports near real-time search, scalable search, and multi-tenancy.

  • Because Elasticsearch is written in Java, it is compatible with almost every platform.

  • Elasticsearch, as a language-independent open-source application, makes it simple to extend its functionality through plugins and integrations.



Apache Kafka is a popular open-source event store and streaming platform written in Java and Scala by the Apache Software Foundation. Thousands of organizations use the platform for streaming analytics, high-performance data pipelines, data integration, and mission-critical applications. It is a fault-tolerant messaging system based on a publish-subscriber model that can handle large data volumes.


Key features include:


  • Scalability with Apache Kafka can be achieved along four dimensions: event processors, event producers, event consumers, and event connectors. This means Kafka scales easily and with no downtime.

  • Due to its distributed architecture, Kafka is highly reliable due to sharing, replication, and fault tolerance.

  • Publish and subscribe to messages with high efficiency.

  • Does not guarantee system failure and data loss.