The Tool Desk
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The list is now a historical snapshot of the enterprise data market in spring 2021. It remains useful for understanding the vendors and technology segments CRN considered important at the time, but it should not be treated as a current 2026 ranking, audited market-share table, product test, or buying shortlist. Read CRN’s original overview.
What was CRN’s Big Data 100?
CRN created the Big Data 100 as an annual vendor guide for solution providers that already operated—or were considering building—a big-data practice. Its scope was deliberately broad. Rather than focusing only on products branded “big data,” CRN included companies involved in storing, processing, integrating, governing, managing, and analyzing enterprise data across on-premises and cloud environments.
That meant the list covered cloud providers, infrastructure and systems companies, database vendors, business-intelligence suppliers, data-integration specialists, machine-learning companies, and newer startups. The commercial opportunity CRN emphasized was the growing need to make distributed enterprise data usable for reporting, operational decisions, analytics, and artificial intelligence.
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CRN published the main article on April 26, 2021, at 10:00 a.m. EDT, with category slideshows released during the same week. The project was therefore a dated editorial selection, not a continuously updated directory.
The five technology categories
| Category | What it covered | Representative vendors named by CRN |
|---|---|---|
| Business analytics | Business intelligence, visualization, reporting, augmented analytics, embedded analytics, and self-service analysis. | Alteryx, AtScale, Databricks, Domo, GoodData, Incorta, Infor/Birst, MicroStrategy, Qlik, Salesforce/Tableau, SAS, Sisense, Starburst, ThoughtSpot, and TIBCO. |
| Database systems | Relational, NoSQL, graph, analytical, and other specialized database technologies. | CRN covered database vendors in a dedicated slideshow, including companies such as Neo4j. |
| Data management and integration | Data movement, integration, quality, governance, cataloging, lineage, and related management tasks. | CRN covered these suppliers in a dedicated data-management and integration slideshow. |
| Big-data systems and platforms | Cloud infrastructure, storage, enterprise data platforms, processing systems, and supporting hardware. | Amazon Web Services, Cloudera, Dell Technologies, Google Cloud, Hewlett Packard Enterprise, Hitachi Vantara/Pentaho, IBM, Micro Focus, Microsoft, Oracle, SAP, Snowflake, Splunk, and Teradata. |
| Data science and machine learning | Data-science environments, machine-learning development, model-building tools, and automation. | CRN covered these suppliers in a dedicated data-science and machine-learning slideshow. |
CRN also noted that some companies span several segments. Those vendors were placed in the category where CRN considered them most prominent. The complete category index is available in CRN’s Big Data 100 overview, with separate slideshows for business analytics, systems and platforms, data management and integration, database systems, and data science and machine learning.
Examples of companies on the list
Cloud, infrastructure, and enterprise platforms
The systems-and-platforms category included broad technology providers such as AWS, Google Cloud, Microsoft, IBM, Dell Technologies, and HPE. It also included data-platform and analytics specialists such as Cloudera, Snowflake, Splunk, Teradata, Hitachi Vantara/Pentaho, and Oracle.
These companies were not interchangeable. A hyperscale cloud provider, an enterprise hardware company, a cloud data warehouse, and an analytical database serve different architectural and commercial roles. Their shared presence on the list reflects CRN’s broad definition of the big-data ecosystem, not a claim that one was objectively superior to the others.
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Analytics and business intelligence
CRN’s business-analytics coverage ranged from visualization and self-service BI to embedded analytics, augmented analysis, and broader data-platform capabilities. Examples included Tableau, Qlik, SAS, Alteryx, Domo, MicroStrategy, Sisense, ThoughtSpot, TIBCO, and Starburst.
The 2021 slideshow also supplied historical context for several companies. CRN described Databricks as founded by developers of Apache Spark and reported that it had raised a $1 billion Series G round in February 2021. It also identified Tableau as a Salesforce company following Salesforce’s reported $15.7 billion acquisition in 2019. Those details describe the 2021 context and should not be read as current company or product information.
Data platforms and query technologies
Snowflake, Databricks, Cloudera, Teradata, Starburst, and Dremio illustrate how the 2021 market was moving beyond traditional data warehouses toward cloud platforms, lakehouse architectures, distributed SQL, and query access across multiple data sources. In CRN’s 2021 coverage, Snowflake’s recent public listing and reported fiscal-year revenue were part of its market context.
The emerging-company section
CRN published a separate slideshow for emerging big-data companies, cutting across the main categories. A CRN France mirror described this group as companies founded between 2015 and 2020. Examples included Ahana, Alluxio, and Dremio.
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Was it actually ranked from 1 to 100?
The project was called the Big Data 100, and CRN described it as an annual list or ranking of important vendors. However, the accessible presentation is organized primarily through category slideshows and does not establish a transparent, comparable numerical score for every vendor.
The most accurate description is therefore CRN’s 2021 selection of 100 big-data technology vendors, organized by category. It is misleading to claim that vendor No. 7 objectively defeated vendor No. 63 unless the original material provides a verifiable and meaningful order. Inclusion indicates editorial recognition, not a measured position in market share, performance, security, customer satisfaction, or value.
Market context CRN cited
CRN cited a ResearchandMarkets forecast that the global big-data market—including products, solutions, and services—would grow from $138.9 billion in 2020 to $229.4 billion by 2025, equivalent to a projected 10.6% compound annual growth rate. This was a third-party forecast reported by CRN, not CRN’s own market measurement and not a verified 2026 result.
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CRN connected that opportunity to rising data volumes, data distributed between on-premises and cloud environments, demand for data processing and management, and the need for analytics and decision support. For channel companies, the opportunity extended beyond resale to implementation, integration, migration, governance, managed services, and specialist expertise.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to use the 2021 list today
Use the list as a historical discovery tool, then perform a separate current evaluation. A sensible process is:
- Start with the workload. Decide whether the need is batch analytics, streaming, BI, machine learning, an operational database, an analytical database, or a lake, warehouse, lakehouse, or hybrid architecture.
- Match the deployment model. Compare SaaS, public cloud, private cloud, on-premises, hybrid, and multicloud options.
- Check integration. Assess connectors and APIs for existing cloud services, ERP and CRM systems, storage formats, streaming tools, BI platforms, identity systems, catalogs, and governance controls.
- Reverify the vendor. Product names, ownership, licensing, cloud availability, leadership, and strategy may have changed since April 2021. Do not assume that inclusion means the company or product remains in the same form in 2026.
- Model total cost. Include consumption charges, storage, data transfer, support, implementation, training, administration, and migration or exit costs—not just the software license.
- Evaluate governance and portability. Check residency, access controls, encryption, lineage, auditability, regulatory requirements, open formats, and the practical difficulty of moving data away.
- Assess channel fit. Solution providers should examine partner terms, certification requirements, services attach opportunities, recurring revenue, managed-service options, margin structure, and vendor concentration risk.
- Validate independently. Request current documentation, product demonstrations, customer references, proof-of-concept results, and current commercial terms. Vendor announcements can confirm inclusion on CRN’s list, but promotional claims about leadership or adoption require separate validation.
Why the list should not be treated as a current buying guide
- It is dated: the list reflects the market as CRN understood it in 2021.
- It is editorial: no detailed scoring rubric or audited ranking methodology is established in the accessible material.
- It mixes unlike companies: cloud platforms, databases, BI products, infrastructure vendors, and startups cannot be compared on a single universal scale.
- Categories overlap: companies such as Databricks, Snowflake, Qlik, TIBCO, IBM, Oracle, and Microsoft operate across multiple data disciplines.
- Inclusion is not proof of superiority: the list does not establish market share, reliability, security, customer satisfaction, performance, or total cost of ownership.
- Historical descriptions need attribution: statements about funding, revenue, product capabilities, or company status should be understood as claims or descriptions from the 2021 coverage unless independently updated.
Bottom line
The Big Data 100 2021 is best understood as a category-based CRN vendor guide for the IT channel. Its value today is historical and navigational: it shows how the enterprise data ecosystem was being organized around cloud platforms, databases, integration, analytics, machine learning, and emerging data infrastructure in spring 2021.
For a 2026 technology decision, use it to generate candidate vendors—not to select a winner. Current product availability, ownership, pricing, architecture, governance, partner economics, and portability all require fresh verification.
Quick Recap
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