A data analytics company is a business whose main product is the collection, processing and analysis of data for other organisations, either as software (a platform on which customers store, query and model data) or as services (consultants and engineers who build analyses, data pipelines and models for clients). This list covers both kinds. It does not cover business intelligence and dashboard tools, which are treated in a separate list of data visualization software, nor general IT outsourcers whose analytics work is a small, unreported part of revenue.
The companies are ordered first by the most recent annual revenue or revenue run-rate they publish, and then, for firms that publish no revenue, by stated headcount. On that basis the platform vendors lead: Databricks reported a revenue run-rate above US$7 billion in August 2026, and Snowflake and Palantir each reported annual revenue of around US$4.5–4.7 billion. Specialist analytics service firms such as Fractal and LatentView are far smaller by revenue but are among the few that publish audited accounts.
Contents
- Platforms and services
- Methodology
- The list
- Comparison table
- Choosing between a platform and a services firm
- Frequently asked questions
- See also
Platforms and services
Analytics platform companies sell the infrastructure on which analysis runs: cloud data warehouses and lakehouses, statistical software and operational AI platforms. Their revenue is usually recurring and, for the cloud-native vendors, consumption-based. Snowflake, for example, bills for the compute and storage customers actually use, while Teradata derives 86.9% of its revenue from recurring sources.
Analytics services companies supply people. Their revenue scales with headcount and they generally build on top of the platforms above. Several service firms in this list describe their work in terms of a particular platform ecosystem; Quantiphi, for instance, was named a Google Cloud Partner of the Year in four categories in 2026. Many organisations use both kinds of company at once: a platform for storage and computation, and a services firm to design and run the analytics on it.
Methodology
Companies were included if their primary business is data analytics, either as a platform (data warehousing, lakehouse, statistical or analytical AI software) or as specialist analytics services, and if they were operating under their current name on 12 November 2026. Business intelligence dashboard tools, covered in a separate list, and diversified IT services groups that do not report analytics separately were excluded.
Entries are ordered in three groups. The first group (ranks 1–8) contains companies that publish a revenue figure, ordered by that figure: audited revenue for the most recent completed fiscal year (December 2025 for Palantir, EXL and Teradata; January 2026 for Snowflake; March 2026 for Fractal and LatentView), the company-reported sales figure for SAS, and the latest company-announced revenue run-rate for Databricks, which is privately held. Figures in Indian rupees were not converted; the order holds at any rupee exchange rate seen in 2025–2026. The second group (ranks 9–10) contains private firms that publish no revenue, ordered by the most recent headcount the company itself has stated. The third group (ranks 11–12) publishes neither figure and is ordered alphabetically. The ranking measures scale, not the quality of work for a particular client.
The list
1
Privately held data and AI platform built on the lakehouse model
Best for: Organisations that want data engineering, warehousing and machine learning on one platform
Databricks sells a cloud platform that combines data engineering, data warehousing, machine learning and generative AI tooling on a single storage layer, an approach it calls the lakehouse. In August 2026 the company said it had crossed a US$7 billion revenue run-rate, with year-over-year growth above 80% in its second quarter. In the same announcement it reported closing a US$5 billion funding round at a US$190 billion valuation, and said more than 20,000 organisations use the platform. Databricks is headquartered in San Francisco. Because it is private, its figures are run-rates published by the company rather than audited annual revenue, which is the main caveat when comparing it with listed peers.
- Revenue run-rate
- Over US$7bn (announced Aug 2026)
- Valuation
- US$190bn (Aug 2026 funding round)
- Organisations using the platform
- 20,000+
- Headquarters
- San Francisco, California, US
- Ownership
- Private
Strengths
- Largest analytics platform in this list by disclosed revenue figure
- Single platform spanning ETL, SQL warehousing and model development
- Consumption pricing scales down for small workloads
Limitations
- Revenue figures are company-reported run-rates, not audited accounts
- Getting value usually requires data engineering skills in-house or through a partner
- Usage-based costs can be hard to forecast without governance
2
Listed cloud data platform with consumption-based pricing
Best for: Enterprises centralising analytics and data sharing in a managed cloud warehouse
Snowflake operates what it calls the AI Data Cloud, a managed service for storing, querying, sharing and applying AI to data across the major public clouds. For the fiscal year ended 31 January 2026 it reported total revenue of US$4.68 billion, up 29%, of which product revenue was US$4.47 billion. The company had 733 customers generating more than US$1 million in trailing twelve-month product revenue and counted 790 of the Forbes Global 2000 among its customers at year-end. Customers pay for compute and storage as they use them rather than through fixed seat licences, which makes revenue sensitive to how heavily customers run workloads in a given quarter.
- Revenue (FY2026)
- US$4.68bn (year to 31 Jan 2026)
- Product revenue (FY2026)
- US$4.47bn
- Forbes Global 2000 customers
- 790 (31 Jan 2026)
- Listing
- NYSE: SNOW
Strengths
- Audited, quarterly-reported financials and customer metrics
- Little infrastructure to manage; runs on AWS, Azure and Google Cloud
- Built-in data sharing between organisations
Limitations
- Consumption billing can rise quickly with poorly optimised queries
- Platform rather than consultancy: implementation is done by the customer or partners
- Competes directly with the cloud providers whose infrastructure it runs on
3
PT
Analytics and AI software for government and commercial operations
Best for: Governments and large enterprises needing analytics tied to operational decisions
Palantir builds software platforms (Gotham, Foundry and its Artificial Intelligence Platform) that integrate an organisation's data into an operational model on which analysts and AI applications can act. Its annual report for 2025 shows total revenue of US$4.475 billion, up 56%, split between US$2.402 billion from government customers and US$2.073 billion from commercial customers. The United States accounted for 74% of revenue and the United Kingdom for 10%. Palantir had 4,429 full-time employees at the end of 2025, and its principal executive offices are now in Aventura, Florida, having previously been in Denver, Colorado. Growth has continued in 2026: third-quarter revenue was US$2.313 billion, up 96%, and full-year 2026 guidance was raised to US$8.530–8.534 billion.
- Revenue (FY2025)
- US$4.475bn (year to 31 Dec 2025)
- Employees
- 4,429 full-time (31 Dec 2025)
- Principal executive offices
- Aventura, Florida, US
- Listing
- Nasdaq: PLTR
Strengths
- Strong record in defence, intelligence and public-sector analytics
- Combines data integration, analytics and AI deployment in one stack
- Fastest revenue growth among the listed companies here
Limitations
- Government customers supplied 54% of 2025 revenue
- Long, high-touch sales and deployment cycles
- Proprietary platform with significant lock-in
4
Long-established statistical and analytics software vendor
Best for: Regulated industries with established statistical modelling and risk teams
SAS develops analytics, statistics, forecasting and machine-learning software, now sold mainly through its cloud-native Viya platform. Its 2025 annual report states that the company again recorded more than US$3 billion in annual sales and remained profitable, with more than half of sales coming from outside the United States. The report cites 20% growth in SAS Viya sales and 22% growth in cloud sales, and notes that SAS was incorporated on 1 July 1976 with four employees. SAS is headquartered in Cary, North Carolina. The company does not publish audited accounts, so only the rounded sales figure is available; it is particularly entrenched in banking, insurance, pharmaceuticals and government, with the report citing more than 2,700 financial-services organisations among its users.
- Revenue (2025)
- More than US$3bn (company-reported)
- Founded
- 1976
- Headquarters
- Cary, North Carolina, US
Strengths
- Deep, validated statistical and risk-modelling capabilities
- Long presence in regulated sectors where model governance matters
- Cloud (Viya) and on-premises deployment options
Limitations
- Only a rounded revenue figure is published
- Licensing is quote-based and generally more expensive than open-source alternatives
- Proprietary SAS language skills are less common among newer analysts than Python or SQL
5
Listed data and AI services firm with a large analytics practice
Best for: Insurers, healthcare payers and banks combining analytics with outsourced operations
EXL describes itself as a global data and artificial intelligence company offering services and solutions. For 2025 it reported revenue of US$2.09 billion, up 13.6%, and guided to US$2.275–2.315 billion for 2026. The company was founded in 1999, is headquartered in New York and states that it has more than 65,000 employees. Unlike the platform vendors above, EXL sells people-led services: analytics, data management and AI model development delivered alongside the operations work it has historically run for clients. That makes it more of an outsourcing partner than a software supplier.
- Revenue (FY2025)
- US$2.09bn (year to 31 Dec 2025)
- Employees
- 65,000+
- Founded
- 1999
- Headquarters
- New York, US
- Listing
- Nasdaq: EXLS
Strengths
- Large, audited services business with sector specialisation
- Can combine analytics with operational delivery
- Offshore delivery scale
Limitations
- Analytics revenue is not broken out separately in the release
- Strongest in a few verticals; less relevant outside financial services and healthcare
- Services model means costs scale with headcount
6
Enterprise data warehouse and analytics platform in transition to cloud
Best for: Large enterprises with existing high-volume warehouse workloads
Teradata provides a data and analytics platform, VantageCloud, used by large enterprises for high-volume analytical workloads in hybrid and multi-cloud environments. Its 2025 annual report shows total revenue of US$1.663 billion, down 5% from US$1.750 billion, with recurring revenue of US$1.445 billion making up 86.9% of the total and consulting services contributing US$201 million. The company had approximately 5,100 employees at the end of 2025, about 30% of them in the United States, and its corporate headquarters is in San Diego, California, where it owns its campus. Declining total revenue reflects the shift from perpetual licences and on-premises systems to cloud subscriptions.
- Revenue (FY2025)
- US$1.663bn (year to 31 Dec 2025)
- Employees
- c. 5,100 (31 Dec 2025)
- Headquarters
- San Diego, California, US
- Listing
- NYSE: TDC
Strengths
- Proven at very large analytical workloads
- Hybrid deployment for organisations not moving fully to public cloud
- Mostly recurring revenue base
Limitations
- Total revenue fell in 2025
- Smaller ecosystem than the newer cloud-native platforms
- Primarily suited to large enterprises
7
FA
Indian-founded AI and analytics services firm listed in 2026
Best for: Large consumer, healthcare and financial firms buying analytics and AI consulting
Fractal provides analytics, data engineering and AI consulting to large companies, alongside a set of AI products. Founded in 2000, it listed on the National Stock Exchange and BSE in India in 2026. For the fiscal year ended 31 March 2026 it reported consolidated revenue of INR 32,997 million, up 19%, and net income of INR 2,868 million, up 30%. The company had six client relationships worth US$20 million or more and 59 worth US$1 million or more, and states that it employs over 5,000 professionals. It reports subsidiaries in the United States, United Kingdom and Australia. Fractal is one of only two pure-play analytics services firms in this list that publish audited revenue.
- Revenue (FY2026)
- INR 32,997m (year to 31 Mar 2026)
- Employees
- 5,000+
- Founded
- 2000
- Listing
- NSE and BSE (2026)
Strengths
- Audited financials following its 2026 listing
- Specialist analytics and AI focus rather than general IT outsourcing
- Long-standing client relationships of significant size
Limitations
- Much smaller than the platform vendors and EXL
- Concentrated in large-enterprise accounts
- Short track record as a listed company
8
LA
Listed analytics and data engineering consultancy
Best for: Mid-size and large firms needing analytics engineering on modern cloud platforms
LatentView offers analytics consulting, data engineering and AI services, largely on top of the cloud data platforms its clients already use. It was founded in 2006 by Venkat Viswanathan and Pramad Jandhyala, became publicly listed in India in 2021, and lists its U.S. office in San Jose, California, with a registered office in Chennai. For the fiscal year ended 31 March 2026 it reported total revenue of INR 10,602 million. The company's own timeline notes that it crossed 1,000 employees in 2022 and operates delivery centres in Chennai and Bengaluru. Its revenue makes it the smallest company in the revenue-ranked part of this list, but it is one of very few analytics specialists with audited public accounts.
- Revenue (FY2026)
- INR 10,602m (year to 31 Mar 2026)
- Founded
- 2006
- U.S. office
- San Jose, California
- Listing
- India (2021)
Strengths
- Publicly listed with audited results
- Specialist focus on analytics and data engineering
- Long operating history since 2006
Limitations
- Small scale compared with most firms here
- Rupee-reported results complicate comparison with U.S. peers
- Limited public detail on client mix
9
Privately held data science and AI services firm
Best for: Enterprises wanting a dedicated analytics and AI engineering partner
Tiger Analytics provides data science, machine learning, data engineering and AI services to large companies. In August 2026 it appointed Prakash Arunachalam, previously president and chief operating officer of Servion, as its global head of operations. In the same announcement the company stated that its team of more than 7,000 technologists and consultants is based in the United States, Canada, the United Kingdom, India, Singapore and Australia. It does not publish revenue, which is why it ranks below the companies that do, despite a headcount larger than several of them.
- Employees
- 7,000+ (Aug 2026)
- Ownership
- Private (revenue not published)
Strengths
- Largest of the private pure-play analytics firms by stated headcount
- Teams on three continents
- Delivery across North America, Europe and Asia-Pacific
Limitations
- No published financial statements
- Headcount is a company round figure
- Large-firm focus may not suit small budgets
10
T
Privately held data science and AI consultancy
Best for: Companies scaling analytics and AI delivery through an offshore partner
Tredence offers data engineering, analytics and AI services. In February 2026 it stated it had more than 4,200 employees across the San Francisco Bay Area, Chicago, Dubai, London, Toronto and Bengaluru, and announced a new centre in Hyderabad, where it planned to grow from more than 400 staff to over 2,200 by 2027. The company does not publish revenue, so it is ranked on stated headcount, which places it behind Tiger Analytics. Its office list spans North America, Europe, the Middle East and India, and the Hyderabad expansion is planned to add about 700 roles in 2026.
- Employees
- 4,200+ (Feb 2026)
- Ownership
- Private (revenue not published)
Strengths
- Publishes headcount and office locations
- Rapidly expanding delivery capacity
- Partnerships with the main cloud data platforms
Limitations
- No published financial statements
- Fast hiring can affect consistency of delivery teams
- Smaller than the largest private rival, Tiger Analytics, by stated headcount
11
MS
Decision sciences firm serving large U.S. corporations
Best for: Fortune 500 companies wanting long-term analytics teams
Mu Sigma describes itself as a pure-play decision sciences company that combines analytics, data engineering and problem-solving methods for business decisions. It states that it works with more than 140 Fortune 500 companies and refers to more than 20 years in the field. The firm, led by founder Dhiraj Rajaram, publishes neither revenue nor a current headcount, so it is placed after the firms that disclose one of those figures.
- Fortune 500 clients
- 140+ (company-stated)
- Ownership
- Private (revenue and headcount not published)
Strengths
- Long-established client base among very large companies
- Pure-play analytics focus
- Single-discipline firm rather than a division of a larger IT group
Limitations
- Discloses almost no financial or headcount data
- Limited public information on recent performance
- Model built around large, long engagements
12
Q
AI and data engineering firm with deep Google Cloud and AWS ties
Best for: Organisations building analytics and AI on Google Cloud or AWS
Quantiphi provides AI, machine learning, data engineering and analytics services, and has operated since 2013. Its 2026 announcements are issued from Marlborough, Massachusetts. Its other 2026 recognition included Google Cloud Talent Development Partner of the Year for Asia-Pacific and a gaming-industry solutions award. In April 2026 Google Cloud named it Partner of the Year in four categories, including Databases Partner of the Year for North America and Country Partner of the Year for Singapore. It does not publish revenue or a headcount, so it is placed alongside Mu Sigma in the final group, ordered alphabetically.
- Founded
- 2013
- Ownership
- Private (revenue and headcount not published)
Strengths
- Strong cloud-provider partner standing
- Combines analytics with applied AI engineering
- Recognised by Google Cloud in several 2026 partner categories
Limitations
- Discloses no financial or headcount data
- Strongest fit for organisations already on Google Cloud or AWS
- Smaller consulting footprint outside North America and India
Choosing between a platform and a services firm
Frequently asked questions
What is the largest data analytics company?
By published revenue, Databricks is the largest company in this list, with a revenue run-rate above US$7 billion announced in August 2026. Among listed companies with audited annual results, Snowflake reported US$4.68 billion for the fiscal year to January 2026 and Palantir US$4.475 billion for calendar 2025. Run-rates and fiscal-year revenue are measured differently, so the comparison is approximate.
What is the difference between a data analytics company and a BI tool?
A business intelligence tool is software for building dashboards and reports on data that is already prepared. A data analytics company, as used here, either provides the underlying platform where data is stored, processed and modelled, or supplies the consultants and engineers who build the analysis. Many organisations use a BI tool on top of an analytics platform.
Is Fractal Analytics a listed company?
Yes. Fractal Analytics, founded in 2000, listed on the National Stock Exchange and BSE in India in 2026. For the fiscal year ended 31 March 2026 it reported consolidated revenue of INR 32,997 million and net income of INR 2,868 million, and it states that it employs more than 5,000 professionals.
Which analytics services firms publish financial results?
Among the specialist analytics services firms in this list, Fractal Analytics and LatentView Analytics publish audited results because they are listed in India, and EXL publishes results as a Nasdaq-listed company. Tiger Analytics, Tredence, Mu Sigma and Quantiphi are privately held and do not publish revenue.
Is SAS a public company?
SAS does not publish audited financial statements and has not listed its shares. Its 2025 annual report states only that it recorded more than US$3 billion in annual sales and remained profitable, with more than half of sales from outside the United States. The company is headquartered in Cary, North Carolina, and was incorporated in 1976.
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