. big-dataThe Big Data space is heating up – to the point that many pundits already see it as the over-hyped heir to “cloud.” The hype may be a bit much, but Big Data is already living up to its potential, transforming entire business lines, such as marketing, pharmaceutical research, and cyber-security. With more than 2.5 quintillion bytes of data being generated daily. It is more than safe to assume that Big Data is gearing up for changing the way we think!

  • The global Big Data and Analytics market is worth $274 billion
  • Around 2.5 quintillion bytes worth of data are generated each day
  • Big Data analytics for the healthcare industry could reach $79.23 billion by 2028
  • There are currently over 44 zettabytes of data in the entire digital universe
  • 70% of the world’s data is user-generated
  • Cloud computing end-user spending totals around $500 billion annually

Hera are the Top Big data companies to watch in 2024.

1. Sumo Logic

What they do: Apply machine learning to data center operations, using data analysis to pinpoint anomalies, predict and uncover potentially disruptive events, and identify vulnerabilities.

Sumo Logic’s Anomaly Detection attempts to solve this pain point by enabling enterprises to automatically detect events in streams of machine data, generating previously undiscoverable insights within a company’s entire IT and security infrastructure and allowing remediation before an issue impacts key business services.

2. Ayasdi

What they do: Apply Big Data analysis in order to solve complex problems, including finding cures for cancers and other diseases, exploring new energy sources, and preventing terrorism and financial fraud.

Ayasdi believes a better approach is to look at the “shape” of the data. Ayasdi argues that large data sets have a distinct shape, or topology, and that shape has significant meaning. Ayasdi claims to help companies determine that shape in minutes so they can automatically discover insights from their data without ever having to ask questions, formulate queries, or write code.

3. Feedzai

What they do: Feedzai uses real-time, machined-based learning to help companies prevent fraud.

It’s no great revelation that online fraud is a major problem. However, its impact is often underestimated. For instance, the Target breach could end up costing as much as $680 million, according to the Ponemon Institute.

Feedzai claims that it can detect fraud in any commerce transaction, whether the credit card is present or not, in real-time. Feedzai combines artificial intelligence (AI) to build more robust predictive models and analyze consumer behavior in a way that mitigates risk, protects consumers and companies from fraud, and preserves consumer trust.

4. CloudPhysics

CloudPhysics goal is to analyze the world’s IT data knowledge and use the information to transform computing, driving out machine and human costs in ways never before possible. Today, their servers receive a daily stream of 100+ billion samples of configuration, performance, failure, and event data from their global user base.

CloudPhysics’ service combines Big Data analytics with data center simulation and resource management techniques. CloudPhysics argues that this approach uncovers hidden complexities in the infrastructure, discovers inefficiencies and risks that drain and endanger resources, and enables what-if analyses that can inform every data center decision.

5. BloomReach

BloomReach Organic Search combines web-wide intelligence and site-level content knowledge with machine learning and natural language processing to predict demand and dynamically adapt pages to match consumer behavior and intent. This helps companies capture up to 60 percent of net-new users. BloomReach also takes a data-driven approach to m-commerce, more accurately matching consumers with content and products. This increases revenue-per-site-visit by up to 40 percent, and drives sales across all shopping channels.

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6. Altiscale

Altiscale service is intended to abstract the complexity of Hadoop. Altiscale’s engineers set up, run, and manage Hadoop environments for their customers, allowing customers to focus on their data and applications. When customers’ needs change, services are scaled to fit – one of the core advantages of a cloud-based service.

7. Pursway

Pursway’s software is intended to improve customer acquisition, cross-selling opportunities, and retention. By imprinting a social graph onto existing customer and prospect data, identifying actual relationships between buyers, and identifying target customers who have a demonstrated influence over others’ purchasing decisions, Pursway argues that it can help consumer-facing organizations close the gap between how businesses market and how people actually buy.

8. PlaceIQ

PlaceIQ says that it “provides a multidimensional depiction of consumers across location and time.” This allows brands to define audiences and intelligently communicate with those audiences to support greater ROI. PlaceIQ’s product, Audiences Now, focuses on targeting customers where they are, in real time, creating an immediacy to a brand’s marketing strategy.

9. MemSQL

Big Data and real-time analytics have the potential to profoundly impact the way organizations operate and how they engage with customers. However, there are challenges that prevent companies from fully extracting value from their data. Legacy database technologies are prone to latency, require complex and expensive architectures, and rely on slow disk-based technology.

10. Couchbase

Couchbase is placing its bet on NoSQL. The startup argues that its NoSQL document-oriented database technology provides the scalability and flexible data modeling needed for Big Data-scale projects. Couchbase also claims to offer the first NoSQL database for mobile devices. Via

11. IBM

International Business Machine (IBM) is an American company headquartered in New York. IBM is listed at # 43 in Forbes list with a Market Capitalization of $162.4 billion as of May 2017. The company’s operation is spread across 170 countries and the largest employer with around 414,400 employees.

IBM is the biggest vendor for Big Data-related products and services. IBM Big Data solutions provide features such as store data, manage data and analyze data.

12. TCS

TCS, a global leader in IT services, consulting, and business solutions, leverages technology for business transformation and helps catalyze change. TCS’ Big Data and Analytics Test Automation Solution or the BITS platform helps companies answer queries around different data formats and outline solutions

13. Infosys

Infosys is a global leader in next-generation digital services and consulting. Infosys’ data analytics consulting can help you maximize revenue and optimize services. Learn how to build an analytics-driven enterprise to monetize data.

14. HP Enterprise

HP Enterprise was acquired by Micro Focus including Vertica

Micro Focus has built up a strong portfolio in Big Data products in a very short time span. The Vertica Analytics Platform is designed to manage a large volume of structured data and it has the fastest query performance on Hadoop and SQL Analytics. Vertica delivers 10-50x faster performance or more compared to legacy systems.

With the help of Big Data software, it enables different organizations to store, analyze and explore data irrespective of the source of data, type of data or location of data.

15. Teradata

Teradata is founded in 1974 with headquarter at Dayton, Ohio. Teradata has more than 10K employees across 43 countries and around 1,400 customers with a Market Capitalization of $7.7B.

Teradata’s Big Data Analytical solutions and a team of experts help different organizations to gain the advantage of data. Teradata portfolio includes various Big Data applications such as Teradata QueryGrid, Teradata Listener, Teradata Unity, and Teradata Viewpoint.

16. Oracle

Oracle offers fully integrated cloud applications, platform services with more than 420,000 customers and 136,000 employees across 145 countries. It has a Market capitalization of $182.2 billion and sales of $37.4 B as per Forbes list.

Oracle’s Big Data industry solutions address the growing demand for different industries such as Banking, Health Care, Communications, Public Sector, Retail, etc. There are a variety of Technology solutions such as Cloud Computing, Application Development, and System Integration.

17. SAP

SAP is the largest business software company founded in 1972 with headquarters in Walldrof, Germany. It has a Market Capitalization of $119.7 billion with total employee count as 84,183 as of May 2017.

SAP helps the organization to turn a huge amount of Big Data into real-time insight with Hadoop. It enables distributed data storage and advanced computation capabilities.

Also read:

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18. EMC

DELL EMC helps businesses to store, analyze and protect their data. It provides an infrastructure to get the business outcome from Big Data. It helps the organization to understand customer behavior, risk, operations. Dell EMC has over 50% growth with Data Analytics.

19. Amazon

Amazon.com founded in 1994 with headquarters in Washington. As of May 2017, it has a Market Capitalization of $427 billion and sales of $135.99 billion as per Forbes list. The total employee headcount as of May 2017 is 341,400.

Amazon is well known for its cloud-based platform. It also offers Big Data products and its main product is Hadoop-based Elastic MapReduce. DynamoDB Big Data database, the redshift, and NoSQL are data warehouses and are work with Amazon Web Services.

20. Microsoft

Microsoft’s Big Data strategy is wide and growing fast. This strategy includes a partnership with Hortonworks which is a Big Data startup. This partnership provides HDInsight tool for analyzing structured and unstructured data on Hortonworks data platform (HDP)

Recently Microsoft has acquired Revolution Analytics which is a Big Data Analytics platform written in “R” programming language. This language used for building Big Data apps that do not require a skill of Data Scientist.

21. Google

Google provides integrated and end to end Big Data solutions based on innovation at Google and help the different organization to capture, process, analyze and transfer a data in a single platform. Google is expanding its Big Data Analytics; BigQuery is a cloud-based analytics platform that analyzes a huge set of data quickly.

BigQuery is a serverless, fully managed and low-cost enterprise data warehouse. So it does not require a database administrator as well as there is no infrastructure to manage. BigQuery can scan terabytes data in seconds and pentabytes data in minutes.

22. VMware

VMware is well known for its cloud and virtualization but nowadays it is becoming a big player in Big Data. Virtualization of Big Data enables simpler Big Data infrastructure management, delivers results quickly and very cost-effective. VMware Big Data is simple, flexible, cost-effective, agile and secure.

It has a product VMware vSphere Big Data Extension which enables us to deploy, manage and controls Hadoop deployments. It supports Hadoop distributions which include Apache, Hortonworks, MapR, etc. With the help of this extension, the resource can be used efficiently on the new and existing hardware

23. Splunk

Splunk Enterprise started as a log analysis tool and expanded its focus on machine data analytics. With the help of machine data analytics, the data or information is usable by anyone.

It helps in monitoring the online end to end transactions; monitor the security threats if any, helps to study customer behavior and helps for sentiment analysis on the social platform. Using the Splunk Big Data you can search, explore and visualize data in one place.

24. Alteryx

Alteryx allows different organizations to take advantage of data from a big data environment. This data again can be integrated with external datasets to gain the maximum value from corresponding data sources

25. iTechArt

iTechArt has been the partner of choice for fast-growing startups and innovative companies since 2002, providing fully dedicated engineering teams and custom software solutions

Their forte is agile dedicated teams of engineers who leverage time-tested big data development services to help clients manage data more effectively and efficiently.

26. InData Labs

InData Labs is a top Big Data and AI technology company. Since 2014, the company has been developing AI-powered solutions and has a proven track record of projects for various industries. InData Labs specializes in AI-powered software development, Big Data, and data science project consulting and development.

27. ScienceSoft

At the forefront of data management and AI since 1989, ScienceSoft is a trusted partner for mid-sized and large businesses to build organization-wide big data platforms and dedicated big data solutions.

ScienceSoft designs, codes, tests, deploys, integrates, monitors, and supports the entire big data ecosystems – from big data ingestion, batch and stream processing modules to analytics and ML.

28. RightData

RightData is a data-focused product company. Our self-service products simplify the complex data operations like data ingestion, unifying, structuring, cleansing, validating, transforming, and load your data into target data platforms.

29. Integrate.io

Integrate.io is cloud-based data integration, ETL, and ELT platform that will streamline data processing. It can bring all your data sources together. It will let you create simple, visualized data pipelines to your data lake.

30. Oxagile          

Oxagile is a full-fledged software development provider with a focus on big data. The company’s expertise covers data engineering, data analysis and data visualization (ML analytics, BI dashboarding), as well as data and pipeline migration.

31. Innowise Group

Innowise Group is a data software development company that helps businesses take advantage of the power of big data. With over a decade of experience, the team has developed a reputation for creating effective solutions that improve business efficiency and help companies grow.

Also read:

Types and Examples of NoSQL Databases

40 Best Free and Open Source NoSQL Databases

Why NoSQL is the future of IoT

Adapting NoSQL Syntax to SQL Databases

MongoDB, Cassandra, and HBase-the three NoSQL databases to watch

5 Questions Enterprises Should Ask When Selecting a NoSQL Database

[Updated on 31 Dec 2023]