a vacuum cleaner vacuums up streams of data. text overlaid:

Best Big Data Analytics Tools

Written By Salvador Tarantino
June 8, 2021

Data can create a key competitive advantage in business today. Utilizing Big Data Analytics Tools we are able to use the huge amounts of data customers produce to increase turnover.

There are several dynamic approaches to analyzing data using big data analytics tools. Big data software can help you understand your customers on a deeper level, boost customer perception, and lead your target customers to your products.

Finding the right big data analytics tools for your business can help you develop a long-term strategy and maximize profitability in your market.

But how do you know which one is the best big data analytics tool for your company?

In this article, we’ll take you through the everything you need to know to make an informed choice. But if you’re just here to compare the features and prices, you can skip to the list of big data analytics tools here.

What is Big Data?

In the simplest terms, big data is a term that describes a large volume of data.

Big data is a dataset that is so massive and so rapidly generated that it cannot be processed using conventional data tools. Once data reaches this level of complexity, big data analytics tools are required to analyze and visualize it.

At this point it is important to make a distinction between 2 types of big data – structured and unstructured data.

  • Structured data – data that fills a specific field within a file or record such as Excel files or databases.
  • Unstructured data – data that lacks a data model while having an internal structure. This constitutes essentially all other forms of data.

80% of data is unstructured, and the volume of unstructured data in the world is growing at a rate of 55-65% per year.

The unstructured nature of this data has historically made it more difficult to analyze. However, with big data analytics tools, both the complexity and the cost of working with unstructured data is now decreasing.

Comparison of Structured Data vs Unstructured Data in a photo explained.
Difference between Structured Data and Unstructured Data – Image from Lawtomated

The size of the dataset is not so important – what matters is what you do with it!

The insight captured in these huge datasets can be used to identify problem areas within a sales process or business practices that may have otherwise done unnoticed.

But in addition to highlighting problems, big also finds opportunities…

Facts About Big Data Analytics

According to a Gartner study, 91% of companies still have not reached “transformational” business intelligence levels. This is because many employees are intimidated by the perceived difficulty of working with big data.

Whilst undoubtedly use of a big data platform is the future, for many, it is also the present. The applications of big data analytics tools are already being capitalized upon in business today:

6 Animated people analysing all the data that big data analytics provides
About 2.5 quintillion bytes of data are produced daily. – Image from Medium

Given the above, the data revolution seems unlikely to let up.

And it could affect your business or industry in unexpected ways. If you find this interesting, keep reading and let us answer burning questions you might have about big data and big data analytic tools.

How Big is Big Data?

90% of the data that exists today has been created in the last 2 years.

There were 5 exabytes of data created since the internet started until 2003. Today, this amount of data is created every two days.

There are currently 60 zettabytes of data in existence. Experts predict that this will rise to 175 zettabytes by 2025.

To put this into perspective. If you wanted to download 175 zettabytes with a 4G connection speed, it would take you about 2.500 years.

Data growth forecast on a graph from 2010 to 2025
Data Growth forecast – Image from IDC Data

There is no official definition of how ‘big’ data has to be to be called “Big”.

To add some perspective, you could upload your computer’s 2 terabyte Hard Drive to a network and share it with your family over all the computers in your house. Technically, this would create a distributed data environment, but most people wouldn’t consider this an example of big data.

Big Data is a concept used to describe a problem for which several dimensions must be solved.

As such, big data is often defined by the 5 V’s model:

infographic explaining the 5 V's of big data
Courtesy of Slideteam

Each of the V’s represents a dimension of the data, and the data analysis required depends on which dimension or combination of dimensions your problem falls under.

The data is characterized by the speed with which it are generated (Velocity), the amount of data in the dataset (Volume), the Variety it contains, the degree of precision it holds (Veracity), and how insightful this data can be (Value).

As evidenced above, when it comes to big data, there are many more factors to consider than when you analyze in a simple Excel pivot table.

What is Big Data Analytics?

Big data analytics is the analysis of a huge amount of collected data in order to systematize it and extract behavioral patterns.

Illustration of how big data can be analyzed and then make decisions based on accurate results
  Big data facilitates decisions based on consumer behavior.
Image by Towards data science

Let’s think about some of this data in a way that’s useful or relevant to marketers, namely, social media and digital marketing.

We all want to know what our potential customers are doing online, but sifting through the noise can be tough when we consider the amount of data generated everyday: 

  • 500 million tweets are sent
  • 3750 million Facebook photos are uploaded
  • 306 billion emails are sent
  • 60 hours of video are uploaded every minute to youtube
  • 95 million photos and videos are shared every day on Instagram

And these are just the major social media platforms. But what can we actually do with all this information?

Here is where big data analytics tools come into play.

Big data analytics tools facilitate innovative data discoveries that would not have been possible without data analysis, providing greater insight during the decision making process.

Big data analytics tools essentially take this data and patterns in our behavior online.

At this point it is important to highlight the two main types of analysis that big data analytics tools can help you with: Advanced Analytics and Business Analytics. Let’s explore…

What are Advanced Analytics and Business Analytics (BI)?

Advanced Analytics and Business Analytics (BI) are both data-oriented solutions that businesses can use to describe complex datasets.

The key difference between the two is that Advanced Analytics contains a further step, using sophisticated data modelling techniques to predict future patterns or events. Whereas Business Analytics focuses on events that happened in the past. 

illustration of key difference between advanced analytics and business analytics
Difference between Advanced Analytics and Business Analytics

Although the difference between the two isn’t so binary, the past-versus-future framing is a good starting point for figuring out how to use these two strategies in your own business.

Business intelligence

Business Intelligence focuses on analyzing historical data, managing day-to-day activities, and guiding near-term forecasting using (mostly) organized data.

When companies want to gather and store data on existing processes, optimize workflows, and monitor existing market benchmarks, they can use business intelligence software.

Advanced Analytics

Advanced Analytics is concerned with forecasting and optimizing the next best step.

Another significant difference is the type of information used. Advanced Analytics data is usually coded information that can be captured using a set of metrics.

Both structured and unstructured data is used in advanced analytics data, adding a level of complexity to the analysis as unstructured data must be transformed before being analyzed.

Gif by GIPHY

Where are Big Data Analytics Tools Used?

Big Data Analytics Tools are used across many industries today. And whilst big data has applications as diverse as congestion management in the transportation industry or predicting seismic activity for geologists, this article focuses on the applications for businesses.

Consider the type of data we are able to collect from online consumers – the purchases we make, the websites we visit, the files we download, every time we click on something.

Essentially, every action we take can be recorded, and this data is accumulating, waiting to be analyzed.

On a macro-scale, this information is very valuable. Understanding how consumers generally behave allows businesses to predict their customers’ behavior.

Before big data analytics datasets of such volume were unusable. Today, they can create opportunities.

An image of a computer, phone, and statistical bars representing big data analytics
Image created in-house

Here are some examples of industries that use Big Data Analytics:


This is perhaps one of the biggest use-cases for Big Data Analytics. The growth of big data analytics tools has facilitated the genesis of the digital advertising industry.

Analysis of consumer data on a large scale has led to massive growth in the area of precision marketing, and in general a move away from traditional mass marketing.

Facebook and Google can track user data to create consumer segments based on demographics, psychographics, geographic, and behavioral patterns.

This data can then be sold to companies aiming to advertise to those consumer segments. This allows those advertisers to target their advertising more effectively when selling through these platforms.


Useful big data in this industry can be customer-related: loyalty program data, local demographic data, purchasing activity. Or customer-unrelated: store inventory, POS, product costs analysis

Analysis of big data presents the opportunity for significant cost reduction for an industry which is suffering from a significant decline.

For example, staffing can be optimized through analysis of consumer shopping patterns. Additionally, spending pattern data allows retailers to manage their inventory without the arduous process of manual stocktake.

[Related Article: The Radically Changing Retail Industry in London]

Communications and Media

Similarly to the advertising industry, big data is often used in Communications and Media to analyze behavioral data and create consumer profiles.

In this industry the consequences of the analysis can be more involved however. Consumer viewing patterns can be used to predict what content will be well-received, and therefore the creative process can be dictated by big data.

Big data can also be used to measure content performance in a novel way. Evaluation of media via sentiment analysis is possible using big data, going beyond the traditional metrics of simple engagement.

This area of data analytics has the potential to develop further as technology advances, with analytics tools able to predict consumer emotions, and tailor their experiences accordingly.

Fraud Detection and Handling

Finance departments are using Big Data Analytics Tools to help prevent cyberattacks and electronic frauds, anticipate data violations before they occur.

Big data can even predict big traffic spikes on servers allowing financial services to prepare for these instances, increasing productivity and reducing operating costs.

The Securities Exchange Commission (SEC) is utilizing Big Data Analytic Tools, Machine learning, and AI to gather information and screen financial markets for conceivable illicit exchanges.

Why do Marketers need to use Big Data Analytics Software?

Consumers are online all day – and this generates huge amounts of data through the different applications that are used.

Big data analytics tools are able to predict consumer trends and adapt their business practices accordingly. For example, the consumer trend towards sustainability has led to the growth of sustainability in marketing.

The modern marketer understands the value of big data to our business decisions – from price optimization to maximizing customer satisfaction and loyalty.

infographic of the benefits of big data analytics
Image courtesy of SAS

The development of big data analytics tools allows marketers to drill down to more specific of Key Performance Indicators (KPIs) involved in almost every aspect of marketing. These KPIs are also more relevant and unique to their business.

The degree to which customer segmentation has been made more accurate and therefore effective is thanks largely to the use of big data. Customer buying personas can be built-out more fully, and segmented by a greater number of variables.

This has allowed marketers to create strategic customer solutions, and ultimately, drive sales.

What are the advantages of using Big Data Analytics Tools?

Having a more complete understanding of the customer allows businesses to provide the most appropriate solution to any customer problem. The following areas have seen the biggest benefit from big data:

Price optimization
Similar to the ‘surge pricing’ you might be familiar with from Uber, big data allows you to manage supply and demand more effectively based on consumer behavior.

Personalization of online shopping
Based on demographic data and an individuals purchasing history, a unique offer can be made for each consumer.

Targeted dynamic advertising
Our behavior online can connote the type of advertising that is most likely to encourage a conversion.

Efficient Product Life Cycles
As big data predicts consumer trends, product developers can estimate when there will be appetite within the market for new products before the decline phase.

Higher ROI
More tailored solutions mean customers are more likely to buy, sooner. This decreases ad spend, increasing ROI.

How are Big Data Analytics Tools transforming Marketing?

Big Data Analytics Tools is the biggest change opportunity for Marketing and Sales departments since the internet.

If you’re an ambitious marketer or sales associate, the good news is there are some pretty ‘easy wins’ to be had with the use of big data software.

Data knows… Courtesy of Giphy

Here are some ways Big Data Analytics Tools is transforming Marketing and Sales:

Consumer Decision Journey

Consumers today use multiple channels and devices, creating huge amounts of data to be analyzed. Big data analysis helps marketers understand the intricacies of the customer journey and the interactions that occur along the way.

This can be applied to a marketers current customers as well as when targeting potential customers.

For a marketing and sales specialists, understanding their customer allows them to personalize every element of the customer journey, and anticipate these interactions before they even occur.

Use of big data and understanding of macro-trends in consumer behavior allows marketers to create smaller and more unique segments. In the future, big data could take an unsegmented market and reduce the segment size to a single individual.

Brand Awareness

An Aberdeen Group retail study showed that “data-driven retailers enjoy a greater annual increase in brand awareness by 2.7 times (20.1% vs. 7.4%) when compared to all others” 

This is a result of awareness campaigns generated using customer insights. An strong understanding of the consumer segment you want to target leads to more tailored awareness campaigns.

A campaign that can be designed and targeted directly towards a particular consumer segment will produce a greater level of brand recall and therefore increase awareness and brand. recognition.

This also increases the ROI of awareness campaigns, as consumers recall the advertisement with fewer repeat viewings when the content is tailored towards them.

Customer Acquisition and Retention

A McKinsey study on big data analytics tools found that “Intensive users of Big Data Analytics Tools are 23 times more likely to clearly outperform their competitors in terms of new customer acquisition

Customer loyalty was also found to increase with the use of big data analytics tools. Consumers demonstrated a clear preference for brands that continued to offer tailored solutions to them.

When your every desire is catered to before you have even expressed it, there is no need to look for a competitor brand.

What functionality can you expect from Big Data Analytics Tools?

Below are some of the ways marketers can make use of Big Data Analytics Tools to provide real value and in terms of profitability and performance.

Dynamic Pricing

McKinsey determined that a 1% price increase translated to a 8.7% increase in operating profits when using a big data platform.

Monitoring and analyzing prices in real-time, marketers can adjust prices responsively based on customer behavior (the aforementioned supply and demand).

Adaptive pricing has the potential to improve profitability, mitigate stock shortages, and generate greater demand for poor performing products when big data analysis is applied.


Analyzing historical data using big data platforms, statistical algorithms can forecast future customer behavior.

This function of big data software has various applications beyond the obvious consequences it has for supply chain management.

Marketers can use this data to define their future marketing strategies, select ranges of products that need to be developed or discontinued, and determine which sales channels are most likely to convert.

Effective Allocation of Marketing ROI

Whilst most marketers might think they have a strong understanding of their ROI, you’d be surprised how much of the costs end up in the ‘Other’ column on the annual budget.

Big data analytics tools can help to allocate spend on various marketing channels with a greater degree of accuracy. This allows marketers to perform an effective cost-benefit analysis of every element of a marketing campaign.

This provides a more holistic and high-level view of overall marketing operations.

Big Data Analytics Tools do not a facilitate a one-step process, but many processes together that encompass many related fields such as data science, business management, and production. 

With that said, we’ve compiled a list of the 22 Best Big Data Analytics Tools so you can choose the best one that best suits the needs of your business.

The 22 Best Data Analytic Tools:

1. Tableau

Tableau's logo

Best Tableau’s Features are:

  • Real-time analysis
  • Data blending
  • Comfortable mobile view
  • Great for beginners (does not require any programming skills to operate)

Tableau is a powerful and fastest-growing big data analytics software utilised in the Business Intelligence Industry.

It assists in analyzing unprocessed data in a quite effortlessly understandable format. 

It also allows non experienced users to modify the platform and create dashboards that facilitate their use.

A photo of Tableaus features showing how the platform looks
Tableau’s platform

Individual plans with one creator costs $70/month, while Duo plans with two creators costs $140/month.

Tableau Explorer costs $35/month and allows you to use full-service analytics to explore trusted data and answer your own questions faster.

Tableau Viewer is available for $12/month and allows you to display and interact with dashboards and visualisations in a stable, user-friendly platform.

All packages are billed annually

There is a 14-day trial period, but no free version of the product.

2. Zoho Analytics

Zoho Analytic's logo

Some of the relevant platform features are:

  • Share insights allowing collaboration
  • Wide range of applications to import data from (locally stored files, cloud drives, local or cloud databases, business applications)
  • Wide range of visualization options (over 40 types of charts)

Zoho Analytics is a self-service, big data analytics tool, and big data platform. The Big Data Analytics Platform lets you connect with a wide range of applications in order to transfer data and create insights with their simple drag and drop application, from locally stored files to files in diverse cloud drive platforms.

A photo of application showing how it looks with some graphs and map showing statistics
Zoho Analytic’s platform

Zoho Analytics offers four price packages.

The basic one costs €30/month and supports two users, 500.000 rows, limitless reports and dashboards, 100+ data connectors, Zoho Apps Connectors, Ask Zia!, regular syncronization, and slideshows.

The standard one costs €60 and includes 5 users, 1 million rows, hourly data synchronization, group support, administrator positions, data alerts, data backups, and access logs.

The most popular is the premium one, which costs €145 and has 15 users and 5 million rows available. Report logo rebranding is possible, including hiding the zoho analytics logo. Private links for your reports and dashboards enable access to reports without a zoho analytics account. With activity logs, you can keep track of everything in your account, including downloads, reports produced, and much more.

The enterprise edition costs €575 and allows you to register 50 users, as well as have 50 million rows and 5x performance in the app and live chat support.

3. Splunk

Splunk's logo

Relevant platform features are: 

  • Real-time analytics and reports
  • Achieving a higher return on investment (ROI) in a slower amount of time
  • Mobile-friendly platform
  • Incorporation of machine learning and AI into your metrics and strategy

“Thinking is good, but knowing is better, and doing is what matters”. Splunk is a Big Data Analytics Software used to make data accessible. Analysing data in real-time bringing data to every question, accelerating digitalization and ensuring business resilience.

A photo of Splunk's platform
Splunk Enterprise

The cost is determined by the amount of data captured, whether you purchase a permanent license or a multi-year license.

For 10GB, the annual cost is about $1200/GB, or $900/GB if you purchase three years.

4. Qlik Sense

Qlik Sense logo

Best Features

  • The click associate engine unifies data sources without risking data loss and provides accurate results.
  • With clicks associative technology and their global search system, you do not have to be a business analyst to get the answers you need.
  • Qlik insight advisor with AI-supported.

Qlik Sense is a big data analytics software platform for self-service analytics with one of a kind associative analytics engine that empowers everyone to see the whole story that lives between their data. With their modern platform, you can see all possible associations that exist in your data.

A photo of Qlik Sense interface showing some charts
Qlink Sense Dashboard

Qlik Sense Business costs $30/month and is paid annually. The cloud solution enables analytics to be operationalized across groups and teams. Modern analytics, associative engine, augmented analytics, and community collaboration is included.

Contact Qlink to obtain a price for the Qlink Sense Enterprise SaaS. This version is a cloud-based solution for scalability and extensibility of analytics across departments and organizations. The Enterprise SaaS version includes all of the features of the Business version, as well as Enterprise governance, expanded capability, and multiple user forms.

5. Talend

Talend's logo containing its initials in orange

Some of Talend’s best features

  • First-ever industry trust score, you can instantly validate whether you can trust your data
  • Application and API integration
  • Integration cloud

Talend is an open-source big data software integration platform that provides Big Data analytics, clean data that follows the guidelines and is accessible for everybody, helping you make the right decision after data is analyzed. Makes the ETL (Extract, Transform, and Load) process simplistic and effective.

Talend's platform showing statistics and analyzed data
Talend’s different dashboards

Talend is available in five different packages from which to choose:

Talend Open Source is available to all users for free.

Stitch Data Loader is a paid version that ranges from $100 to $1,000.

Talend Pipeline Designer has hourly pricing dependent on consumption.

Talend Cloud Data Integration costs $1170 per month and $12000 per year (save 15%). Talend Studio and Pipeline Designer licenses are included.

Talend Data Fabric supports big data integration, data governance, application integration, and platinum customer service support. This version comes with both the Talent Studio and the Pipeline Designer licenses.

6. Cassandra

Cassandra's logo

Cassandra’s features:

  • Impressive scalability opportunity 
  • Fast Linear-scale Performance
  • Provides lower latency for its users
  • Cassandra can compress up to 80% of data
  • It was designed to run on cheap hardware which means you don’t need a super CPU to do so

Cassandra is a distributed database management system tailored for when you need scalability without compromising performance in your business. In addition, is the best in its category thanks to its replication of data on several nodes that guarantees no point of failure.

An image of Cassandra's features showing what the platform is capable to do
Cassandra’s features

There is both a free version and a paid version.

There is no free trial for the paid version. (CS team needs to be contacted).

7. Apache Spark

Apache Spark's logo

Apache Spark’s features

  • Write applications quickly in Java, Scala, Python, R, and SQL.
  • Runs 100x times faster using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine.
  • Includes a variety of application programming interfaces (APIs) to bring the best out of spark to its audiences
  • Machine learning, AI
  • Spark Streaming

Apache Spark is an ultra-fast open source Big Data Analytics Platform that holds machine learning and AI applications.

It can handle both real-time analytics and data processing workloads. As a result, Apache Spark combines data and AI so using Spark you can do large-scale data transformations and analysis and immediately run AI algorithms on it.

Illustration of the features of apache spark to show what the platform is able to do
Apache Spark’s features

Apache Spark is free to use.

8. Apache Hadoop

Apache Hadoop's logo

The Hadoop ecosystem provides diverse features including: 

  • Its architecture requires high levels of expertise to use efficiently.
  • Fault tolerance
  • Cost-effective
  • Scalability

Suitable for Big Data analysis

Apache Hadoop is an open-source framework that offers simple programming models allowing users to have highly reliable distributed processes of data, from gigabytes to terabytes.

It provides building blocks on which applications and other services can be built.

An illustration showing what Apache Hadoop is able to do
Apache Hadoop ecosystem

“Spark vs Hadoop” is a frequent search on the web, and is important to mention that Spark is not a modified version of Hadoop. Spark is more of an improvement to Hadoop’s native data processing component, MapReduce.

The price of Apache Hadoop is US $1000 a terabyte.

9. Qubole

Qubole's logo

One of the best features of Qubole are:

  • Single platform for many uses
  • Cost efficiency
  • SLAs & performance
  • Optimized for the cloud
  • Auto-scaling technology

Qubole is a Big Data Analytics Software solution to power your data activation strategy, to take advantage of your growing data warehouses, and data lakes.

Autonomous and self-optimizing make it a single platform for many business cases. Capable of working with cloud providers.

It also includes features like Workload Aware, Autoscaling, and Spot Management. TCO management with Qubole Cost Explorer, adaptive serverless infrastructure, and customer service are all included.

An illustration of Qubole's features displayed with different images and text
Qubole’s features

Qubole’s Enterprise Edition costs $0.168 per Qubole Computer Unit and requires annual payment.

Qubole has a free trial version in which you get a full-featured experience for 30 days and a test-featured setting for two weeks. It also comes with a MasterClass, which is an immersive hands-on environment for getting acquainted with the app.

10. Arcadia Data

Arcadia's Data logo

Some of its features include: 

  • On cluster security and real-time understanding of the data as well as a real-time streaming visualization
  • Big Data Analysis and linear scaling
  • Instant visuals
  • No coding required
  • Customization of the views

If you are feeling somewhat intimidated by Big Data, the Arcadia business intelligence and Big Data Software might help you. 
They take a fundamentally new approach to deliver. Arcadia is the first visual analytics software native to big data, running directly within modern data platforms. It gives their users faster performance and better results.

4 photos of arcadia's data different dashboard and options showing the capability of the platform
Arcadia Data’s interface

The big data platform is available in two versions: Enterprise and Instant. The Instant edition is free and it offers a variety of tools, including connect, which allows you to access data within and outside of Hadoop, Kafka, and the cloud directly from your web browser without the need for driver download.

Discover is a function that helps you to search data sources, structure, and information with complete granularity and clarity, as well as Model and Visualize.

Enterprise is the paid version, it has many additional features such as automated implementation and reporting, certified integration with Apache Ambari and Cloudera Manager, and the ability to scale linearly to billions of records with native, in-cluster execution.

It also has the ability to optimize and accelerate output by self-learning of commonly used queries and dimensions, which are automatically modelled and stored in memory.

11. Sisense

Features of Sisense: 

  • AI-powered insights
  • Enhanced live data experience
  • Query lengths reduced by up to 70%
  • Super-fast dashboards and no skills needed
  • Connection extensibility
  • Possibility to generate great PDFs with its engine

Sisense is a Big Data Analytics Software built custom analytics for everybody, including actionable intelligence that provides data preparation.

It also provides end-to-end solutions while maintaining a moderate software cost.

What can you do with Sisense? – Video by Sisense

Sisense big data software takes its pricing from the amount of data that you manage, so you can expect a very fair price when the bill comes. It also offers a free trial version.

To obtain the full price for their business edition, contact Sisense sales staff to discuss a solution suited to your consumption and desires.

12. Cloudian

Cloudian's logo

Cloudian’s features are: 

  • Enterprise data protection
  • Secure multi-tenancy
  • Data spill protection
  • AD/LDAP Authentication
  • Identity Access Management (IAM)

Cloudian is a Silicon Valley-based Big Data Platform that brings simplicity and performance, specialising in S3 compatible storage systems, multi-tenant and multi-datacenter hybrid cloud storage software. 

Cloudian allows customers to prepare and engage with today’s explosive amount of data and growth, making a platform where structuring data is easy and convenient.

A photo of Cloudian's dashboard showing different analytics
Cloudian’s Dashboard

Cloudian’s big data platform does not have a set price, contact their sales staff to personalize a solution for you.

A free version encourages you to try their datacenter for 45 days to see how simple it is to create your own private cloud. The free trial contains the following features: HyperStore – Enterprise Object Storage and HyperIQ – Analytics and Observability

13. Oracle

Oracle's logo

Some of Oracle’s features are: 

  • Scalability and performance
  • Availability of real-time applications
  • Back up and recoveries
  • Security
  • Oracle can run in different operating systems: Windows Server, Unix, and Linux
  • ACID-compliant

Oracle is a multi-model relational Big Data Software. Became the first one to support Structured Query Language (SQL), which nowadays is industry standard. It is mainly designed for enterprise grid computing making it one of the first choices for cost-effective solutions.

A photo of Oracle's dashboard showing how the interface looks
Oracle’s Dashboard

Oracle’s big data platform is upfront with their cloud pricing; in particular, they have a webpage where they display every comprehensive Cloud usage, including the unit price and the metric used to measure it, which can be “Usage per month,” “Hosted environment per hour,” or “OCPU Per Hour.”

14. Google Big Query

Google BigQuery's logo

Google BigQuery features are:

  • Ability to analyze petabytes of data at impressive speeds and without over throttling with ANSI SQL.
  • Great scale analytics at a cost 26 to 34 percent lower than other alternative cloud store solutions
  • Automatic data transfer service
  • Connect with google products
A photo of Google BigQuery platform showing different statistics
Google BigQuery Platform

BigQuery charges for data collection, streaming inserts, and querying data, but it is free to load and export data.

Data pricing starts at $0.02 per GB per month and goes down to $0.01 per GB per month for “long-term storage,” which Google uses where any database or table partition has not been changed for 90 days in a row.

The cost of a streaming insert is $0.01 per 200 MB.

15. Tibco Spotfire

Tibco Spotfire's logo

Tibco Spotfire features:

  • Seamless user interface 
  • Flexible data architecture
  • Data visualization made easy
  • Machine learning and location analysis for Big Data

Tibco Spotfire is a Big Data Platform tool for Hadoop and sources of big data

It keeps the total cost low as it allows users to build thousands of reports and publish them on its platform. Tibco comes with an agile platform capable of advanced analytics workflows that can be applied to big data in many ways.

A photo of 4 computers showing different dashboards showing its interface
Tibco Spotfire Dashboards

Tibco’s big data software has four models and a 30-day trial period that provides 250 GB of storage for a whole team.

  • Library Storage is $25 per month or $250 per year for 25GB of storage
  • Consumer is $25 per month or $250 per year for a view-only option
  • Business Author is $65 per month or $650 per year for 100 GB including for each Business Author position
  • Analyst is $125 per month or $1250 per year for 250GB included for each Analyst seat.

You can still contact the Sales team to get a customised quote.

16. Aster Database

Aster Teradata's logo

Aster Database features:

  • 90x times faster performance
  • Efficient, linear scaling
  • Fast, easy development
  • Unlimited parallelism 

Aster Database provides a Big Data Software platform. Is a software solution that uses both MapReduce and SQL analytics to process the data for a better understanding of multi-structured data sources with performance and scalability. Additionally, it supports Unix/Linux/ and Windows server platforms.

A photo of Aster Teradata's features showing what the platform is able to do
Aster Teradata

You can download Aster Database free trial version.

For the subscription, the sales team needs to be contacted.

17. Fusionex Giant

Fusionex Giant logo

Features of Fusionex Giant:

  • It allows you to create easy-to-understand visuals.
  • Automatically extract social media content
  • Utilize advanced statistical models
  • Configure active alerts to trends in SoMe
  • Platform available in many languages

Fusionex Giant is a Big Data Software that allows you to find trends in data faster with the help of its natural language processing (NLP). Provides a powerful engine for Social Media (SoMe) monitoring that helps you detect the sentiments and reviews of what people think about your business.

A photo of their website showing all the capabilities and features of the platform
Fusionex Giant Features

To get access to the big data platform you can get in contact with them and present your case.

18. Cleo

Cleo's logo

Cleo features

  • 80% faster issue resolution
  • 40% total cost of ownership reduction
  • end-to-end integration visibility to see errors and resolve issues
  • Cleo Integration Cloud (CIC)

Cleo is a Big Data Analytics Software solution available on Mac, Windows, Android, iPhone, and SaaS that lets you redefine B2B integration with Cleo Integration Cloud (CIC). Helping you improve productivity with its EDI, API, and file-based integrations into a single software platform with ease of use.

A photo of Cleo's dashboard opened in a laptop computer showing different statistics, and capabilities of the platform
Cleo’s dashboard

You need to contact Cleo’s team to get a personalized price for you.

19. AtScale

AtScale's logo

Features of AtScale: 

  • AI and Machine learning
  • The data has autonomous engineering via both SQL and MDX
  • Ability to Drop-in gateway node deployments
  • Google global mobility data

AtScale is a single base Big Data Software that helps you make better business decisions. Helps you modernize your data architecture to help you embrace cloud solutions with reduced complexity while maintaining security and data source fluidity with AI and machine learning.

A Screenshot of At Scale dashboard showing different statistics
At Scale dashboard

The price of AtScale needs to be requested by their team, they will evaluate your business and advanced analytic needs.

20. Ideata

Ideata's logo

Features of Ideata:

  • Data preparation interface. 
  • Machine Learning algorithm (compatible with drag-and-drop)
  • +50 pre-built data connectors
  • Schedule data import
  • Visualize and Share
  • Clustering
  • Smart dashboards

Ideata Analytics is a unified business intelligence platform that provides better connectivity to data thanks to their pre-built data connectors, allowing you to connect from your data source of choice (Oracle, MS SQL Server, Hadoop, Mongo DB, Cassandra, excel, etc). 

Data analytics are made easy with the platform that supplies diverse methods of analyzing and presenting data, making your story understandable.

A photo showing how the ideata's platform work
Ideata’s platform

Contact Ideata for pricing and subscriptions suitable for your business.

21. Zoomdata

Zoomdata's logo

Zoomdata features:

  • Modern BI and data visualization
  • Streaming analytics
  • Blended Analysis
  • Possibility of creating engaging and creative dashboards
  • Modern query engine

Zoomdata is a Business Intelligence (BI) tool that focuses on providing visualization solutions for big and fast data at super-fast speeds. It connects to a variety of data sources, including cloud data stores, NoSQL, Hadoop, Spark, SQL MPP, and traditional databases.

A picture showing the dashboard of zoomdata's
Zoomdata’s dasboard

Zoomdata provides a 30-day free trial.

Fill out a form to get a personalised price depending on how much data you need to analyse in your business.

22. PanBI

PanBI analytics logo

PanBI features:

  • Flexible external API integration capabilities
  • Mobile platform
  • Dynamic schema editor able to support ETL processes 
  • Extensive search and filtering
  • Customizable and exportable dashboards

PanBI’s platform provides a business intelligence solution, including big data analytics as well as a range of other data tools. Moreover, users can harvest datasets from multiple sources simultaneously like SQL, relational databases, and secured/public REST URIs.

A picture showing PanBI's platform on a laptop computer
PanBI’s platform

To access PanBI and its features, you need to fill a form to contact the team. The tailored solution and data consumption will determine the price.

PanBI does not offer a free trial period.


Are you sure you are making the right decisions?

Basing decisions on unreliable information or ‘gut instinct’ can significantly damage your business and your brand if you make the wrong call.

Data technology is evolving at a breakneck pace, and whilst data never lies, almost 70% of data specialists don’t trust in their organization’s data.

Many businesses mistrust their most valuable asset, when they should depend on data to make strategic decisions and propel their company forward.

This is what big data analytics tools are here for. Confidence that every decision you make based on real data, analyzed by algorithms, machine learning, and AI..

 Big data analytics tools represent a future in which there are no more unknowns.

So what are you waiting for? Get involved in the data revolution today!

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