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7 Trending Big Data Tools and Technologies

 July 8  | 0 Comments

As per the Gartner report about big data skills, 2/3rd of big data skill job profiles remains vacant which means that only 1/3 are met. The numbers are an indication of the scarcity of skilled professionals in the market. However, it is a great sense of relief for aspirants as the job openings are abundant. This, in turn, has created a need for professionals with big data skills like Hadoop, Spark, NoSQL, Data Mining, and others.

There are a variety of job opportunities that are up for grab. Some of the job roles are as follows: Hadoop Developer, MapReduce Application Developer, Hadoop Administrator, Java Hadoop Lead, etc.,

In this article, I speak about seven big data tools and technologies that are used by successful analytics developers and organizations and can earn you a lucrative job.



The High-availability distributed object-oriented platform, popularly known as Hadoop, is a software framework that evaluates structured and unstructured data.

  •   Due to Hadoop, data scaling is possible without the threat of hardware failures.
  • It offers huge storage for a variety of data
  •  It can virtually handle infinite coexisting tasks.

With time, Hadoop has evolved. It now includes entire system of interlinked software. This is the reason why lucrative big data solutions depend upon Hadoop. In fact, Zion Market Research estimates that market for Hadoop-based products and services will augment up to 50 % CAGR by 2022. The worth of these products will be around $87.14 billion in 2022, in comparison with $7.69 billion in 2016.

Salary: Proficient Hadoop professionals earn up to $121,313.



It is an agile, principal NoSQL, open-source document database that is cross-platform compatible. MongoDB is famous because of its storage capacity and its role in the MEAN software stack. It stores the document data in the binary form of JSON document, which is otherwise the BSON type. MongoDB is mostly in use for its high scalability, obtainability, and presentation.

This document database has some remarkable inbuilt structures which make the database apt for businesses to make instantaneous decisions, create custom-made data-driven connections with its users. Other than MEAN stack the database is compatible with .NET applications, the Java platform, and others.

Salary: Professionals with niche skills in MongoDB earn up to $117,000.



It is data warehouse tool, built on the Hadoop platform. Apache Hive is a component of Hortonworks Data Platform (HDP). It provides a similar interface as SQL- to store data in HDP. The query language that is exclusive for Hive is HiveQL. This language interprets SQL-like queries into MapReduce jobs then deploy it to Hadoop platform. HiveQL as well supports MapReduce scripts which could be the plugin for queries. Hive augments the schema design elasticity and contributes for data serialization and deserialization.

Salary: Professionals with niche Hive skills make up to $120,873.



Apache Spark is one of the major open source projects for data processing. It has similarities with MapReduce, however, it outpaces MapReduce with features like speed, easy user interaction, and ingenuity of analytics. Apache Spark reduces the development time that Hadoop usually takes. This leads to smooth streaming as well as collaborative analysis of data.

Spark has cohesive units for streaming, graph processing, and SQL sustenance. This is the reason for its entitlement as one of the fastest engine for big data processing. It supports all key big data languages like Python, R, Java, and Scala.

Salary: Professionals possessing knowledge about Spark earn an average salary of $105,000.



Apache HBase is an open source NoSQL database, offering real-time read/write provision to large datasets. It is a Hadoop application that works over HDFS. It scales itself linearly to manage large data sets with numerous rows and columns, and smoothly syndicates data sources of various sources with distinctive structures and schemas. HBase is one of the Apache Hadoop add-ons. It contains tools like Hive, Pig, and ZooKeeper.

Businesses employ Apache HBase’s low expectancy storage for situations that demand real-time analysis and horizontal data for consumer applications.

Salary: Professionals with niche Hbase skills will earn an average salary of $123,934



Apache Cassandra™ is a top-notch Apache project, with its origin at Facebook. It was then built over Amazon’s Dynamo and Google’s BigTable. It is known for its effective management of large chunks of data. Further, Cassandra offers high availability and scalability with no single point of failure in the functioning of server hardware and cloud infrastructure.

Some of the key benefits of Cassandra are its latency, fault permissive, regionalization, proficient sustenance, robustness, flexibility, and scalability.

Salary: Cassandra Developer salary range in the United States ranges from $104,000 – $125,000



Kafka is open source, partitioned, scalable, flaw permissive, highly swift and secure platform. It is important acts as a bridge between several key open source systems like Spark, NiFi, and the third-party tools.

Kafka has similar features as that of a messaging system, with some additional and distinctive features. It preserves feeds of messages into themes. Producers fundamentally pen down the subjects and consumers read those subjects. Since Kafka is a distributed system, subjects are segregated and simulated across numerous nodes. Messages are merely byte collections and developers could use it to stock any object in any format. Usually, String, JSON, and Avro are the most common ones.

Salary: Proficient Apache Kafka professionals earn up to $122,728

Certification Matters

Currently, the job opportunities are flooding for Hadoop skills in India. As per the stats by LinkedIn, Hadoop is leading the board of Big Data tools. Now, speaking about certification, it is significant because it portrays that the skills are taught by industry experts as per the current market trends. We at Acadgild, offer certification training in Hadoop – Big Data and Spark with mentors who have profound knowledge about the subject with decent working experience in the subject. The course curriculum is made in a way that it help students survive and prosper in the Big Data sector.