Cloud Database Report: Oracle, AWS, and Snowflake Take on All Challengers

By: John Foley

Cloud Database Report: Oracle, AWS, and Snowflake Take on All Challengers

By: John Foley

THE PLAYERS

Cloud Database Top 20

The cloud database market is growing and changing, as incumbents led by Oracle compete with the Big 3 cloud service providers—AWS, Google, and Microsoft—and dozens of specialists and startups. 

The innovations are coming fast and furious. I wrote recently about 10 major advances that hit the market in a single month, including a serverless vector database, a fully managed graph database, and Oracle’s latest “converged” database. The database market has been prolific in this respect for years. Carnegie Mellon University tracks a whopping 740 database management systems in its Database of Databases

With so many options, how does an organization choose the best one for its particular needs? The Cloud Database Report has identified 20 cloud database providers that, in our analysis, are the leaders. They represent a cross-section of the market—the incumbents, the cloud service providers, and the challengers. 

We used four criteria in choosing the Cloud Database Top 20: 

  1. Enterprise capabilities. Vendors with a complete range of services and support that enterprises may want or need. Fully managed services are a plus. 
  2. Platform adaptability. Tools, services, and APIs for data integration/migration and application compatibility are must-haves. 
  3. Innovation. A steady pipeline of new, modern, differentiating capabilities. 
  4. Demonstrated business value. Customer success is the #1 proof point. 

 

Deeply rooted incumbents

Conventional wisdom has it that “old guard” vendors like Oracle, IBM, and Teradata, which have been selling database systems for 30-plus years, are vulnerable to being displaced by newer, cloud-native technologies. The reality is that it’s not easy to uproot installed databases or vendors. There may be years of investment, organizational experience, skills, tools, and infrastructure associated with existing database environments. And data migration and applications compatibility are barriers to change. 

With its worldwide installed base, Oracle is a natural target for other cloud database companies. The slings and arrows go something like this: “Oracle is a legacy DBMS and expensive.” AWS CEO Andy Jassy recently called Oracle an “unhappy place” for customers. 

But Oracle has proven to be resilient, both in maintaining its on-premises customer base and competing in the cloud. In Q2 of FY2021, Oracle reported that consumption revenue was up 64% for Oracle Autonomous Database and 139% for Oracle Cloud Infrastructure. Not bad for a “legacy” software company. 

The competitive landscape is like Abbott & Costello’s Who’s on First. When Larry Ellison was asked about Oracle’s ability to compete with cloud-first competitors, he responded that Snowflake “doesn’t remotely compare” to Oracle’s Autonomous Database. Instead, Ellison said, Snowflake was “just killing” Amazon Redshift. 

Snowflake sees AWS, Azure, and Google Cloud as its most immediate competitors. “Our competitive environment is very much dominated by the public cloud vendors,” CEO Frank Slootman told analysts. 

In summary: Snowflake is going after AWS, Microsoft, and Google Cloud. Those cloud leaders all want a piece of Oracle’s customer base. And Oracle, according to Ellison, is in a class of its own. For more on this, see my blog post “Can Oracle Beat AWS and Snowflake in the Cloud Database Wars?

 

Stalwarts and startups

Other vendors are refining their own competitive advantages. Teradata, once the epitome of an on-premises data warehouse vendor, recently announced availability of its cloud data analytics platform, Teradata Vantage, on Microsoft’s and Google Cloud’s marketplaces, added support for more data sources, and introduced a free cloud trial of Vantage. 

At the same time, cloud database startups are driving innovation with new products and business models. In January, Cockroach Labs announced it raised another $160 million in funding for its SQL database. Shortly thereafter, Databricks disclosed $1 billion in series G funding, with AWS, Microsoft, and Salesforce among the investors. 

Some cloud database startups have not yet earned their stripes in the enterprise, but that may just be a matter of time. Fauna, Firebolt, and Pinecone Systems are among the up-and-comers worth watching. 

THE PLATFORMS

AWS CEO Andy Jassy said it's folklore to believe Amazon takes over industries
AWS CEO Andy Jassy

Everything is a platform. The cloud database market has fully embraced this meme and with good reason—it’s what enterprise customers want and need. Teradata describes itself as a cloud data analytics platform. InterSystems is a cloud-first, next generation data platform. Splunk is the data-to-everything platform. 

The platform model one of the great advantages of the cloud. It’s much easier for vendors to assemble comprehensive database platforms using software-as-a-service tools and partnerships, and for customers to import data from disparate sources, run algorithms, distribute data across geos, and more. The Cloud Database Top 20 are heavily weighted toward such platforms. 

Let’s look at Snowflake, which touts its ability to “eliminate data silos and run your workloads from a single platform.” Snowflake is a data warehouse, but it’s more than that. Snowflake’s architecture includes infrastructure capabilities such as storage and compute, pipelines to external data lakes, a marketplace where users can access hundreds of third-party data sets, and integration with machine learning tools and libraries. 

That is a bona fide cloud data platform, and there are others. CIOs and CTOs care about the full range of platform capabilities because it’s often the surrounding tools and services—things like data lakes and built-in machine learning—that account for the greatest business value. If data integration is fast and easy, if third-party analytics tools are a click away, if redundancy can be improved with multicloud capabilities, all of that results in less complexity and faster pay off. 

 

Purpose-built versus all-purpose

As the competition intensifies, a few battle lines have formed. One is SQL vs. NoSQL, which pits traditional relational databases against document databases and graph databases, for example. SQL, of course, is the widely used Structured Query Language.

But this is a fuzzy and even shifting line because NoSQL does not mean “no” SQL, as it seems to imply. Rather, NoSQL is short for “not only SQL.” Many NoSQL databases do in fact work with SQL queries. And a handful of the cloud database providers in our Top 20, including AWS, Google Cloud, IBM, Microsoft, and Oracle, offer both SQL and NoSQL options. Of the top 10 databases in DB-Engine’s database ranking (based on popularity), all support SQL or SQL-like queries.  

Another way to look at the cloud database decision has to do with the types of data and workloads to be managed. AWS, with 15+ databases in its portfolio, has thrown its weight behind the “purpose-built” model. Oracle, meanwhile, promotes its flagship system as a “converged” database that is well-suited for myriad data types and workloads. 

Here too, the line separating these two database styles is not sharp. Multimodel databases are something of a middle ground, capable of managing various data types, data models, and workloads, providing flexibility where needed. The database decision often comes down to the nature of the application supported and performance requirements. 

Google Cloud leans in the direction of purpose-build databases. For example, Google’s Cloud Bigtable excels at high-scale analytics and operational workloads, while Firestore is a NoSQL document database for new applications. 

“Most developers do not say, ‘I want one database for everything,’” Google Cloud director of product management for databases, Kelly Stirman, told me in a briefing for this report. A particular database may be ideal for one application, but not well suited for others, he said. “I don’t think you can engineer one database that serves all of them well.”

That said, Google’s Cloud SQL and Cloud Spanner databases are capable of handling a widening array of workloads in the same way multimodel databases do. 

Many IT organizations will not limit themselves to a single cloud database or cloud database provider but will use the best platforms for the job. We know that many companies already use several cloud service providers for SaaS, PaaS, or IaaS, and the same could happen with cloud databases. The trick is to avoid the complexity of that past that turned corporate data centers into spaghetti bowls of hardware and software. 

 

Key architecture components

An adaptable cloud database architecture is vitally important to reaping the benefits of the cloud database model without recreating the problems of the past. Here are key capabilities to consider:  

  • Hybrid. Few organizations are 100% cloud. The ability to connect existing, on-prem systems with the cloud database is a vital intersection point. This is IBM’s big play in the market with its RedHat stack. Other vendors, including AWS and Oracle, are expanding their hybrid cloud offerings. 
  • Multicloud. The ability to share data and connect databases across clouds is a practical requirement, and there are strategic benefits as well, such as being able to operate in the cloud of your customer’s choosing. Google with Anthos and MongoDB with multicloud clusters are among those promoting multicloud as a differentiating capability.  
  • Multimodel. Many cloud databases support multiple data types, but they do not all support the same data types. It’s important to assess strengths and weaknesses. 
  • Fully managed. Some cloud databases are self-managed by the user, some managed by the service provider, and a few such as Oracle Autonomous Database are fully automated. 

 

Data portability and applications compatibility hinge on having an adaptable architecture and the necessary tools. Virtually all of the cloud database providers offer data-migration tools and services to facilitate the shift of database workloads to their platforms. 

In December, AWS announced expanded options (for both source and target databases) for its AWS Database Migration Service, which has been used to migrate 350,000 databases to AWS. To spur migration to its platforms, AWS makes DMS available at no cost for six months to companies moving databases to Amazon Aurora, Amazon Redshift, Amazon DynamoDB, or Amazon DocumentDB. 

In November 2020, Google introduced a preview of its own Database Migration Service. When generally available, Google DMS will make it easier to move MySQL, PostgreSQL, and SQL Server workloads to Google’s Cloud SQL. Other vendors have similar tools. 

A word of caution: Strategies around compatibility and interoperability are sometimes easier said than done. In one example, AWS says Amazon DocumentDB supports MongoDB 4.0 compatibility for the vast majority of the applications, drivers, and tools “with little or no change.” However, based on its own compatibility testing, MongoDB reports that Amazon DocumentDB 4.0 fails 63% of the MongoDB API correctness test.

Users will need to do their homework as they consider migrating to new cloud database platforms.  

Cloud Database Top 20

THE PLAYERS

The cloud database market is growing and changing, as incumbents led by Oracle compete with the Big 3 cloud service providers—AWS, Google, and Microsoft—and dozens of specialists and startups. 

The innovations are coming fast and furious. I wrote recently about 10 major advances that hit the market in a single month, including a serverless vector database, a fully managed graph database, and Oracle’s latest “converged” database. The database market has been prolific in this respect for years. Carnegie Mellon University tracks a whopping 740 database management systems in its Database of Databases.

With so many options, how does an organization choose the best one for its particular needs? The Cloud Database Report has identified 20 cloud database providers that, in our analysis, are the leaders. They represent a cross-section of the market—the incumbents, the cloud service providers, and the challengers. 

We used four criteria in choosing the Cloud Database Top 20: 

  1. Enterprise capabilities. Vendors with a complete range of services and support that enterprises may want or need. Fully managed services are a plus. 
  2. Platform adaptability. Tools, services, and APIs for data integration/migration and application compatibility are must-haves. 
  3. Innovation. A steady pipeline of new, modern, differentiating capabilities. 
  4. Demonstrated business value. Customer success is the #1 proof point. 

 

Deeply rooted incumbents

Conventional wisdom has it that “old guard” vendors like Oracle, IBM, and Teradata, which have been selling database systems for 30-plus years, are vulnerable to being displaced by newer, cloud-native technologies. The reality is that it’s not easy to uproot installed databases or vendors. There may be years of investment, organizational experience, skills, tools, and infrastructure associated with existing database environments. And data migration and applications compatibility are barriers to change. 

With its worldwide installed base, Oracle is a natural target for other cloud database companies. The slings and arrows go something like this: “Oracle is a legacy DBMS and expensive.” AWS CEO Andy Jassy recently called Oracle an “unhappy place” for customers. 

But Oracle has proven to be resilient, both in maintaining its on-premises customer base and competing in the cloud. In Q2 of FY2021, Oracle reported that consumption revenue was up 64% for Oracle Autonomous Database and 139% for Oracle Cloud Infrastructure. Not bad for a “legacy” software company. 

The competitive landscape is like Abbott & Costello’s Who’s on First. When Larry Ellison was asked about Oracle’s ability to compete with cloud-first competitors, he responded that Snowflake “doesn’t remotely compare” to Oracle’s Autonomous Database. Instead, Ellison said, Snowflake was “just killing” Amazon Redshift. 

Snowflake sees AWS, Azure, and Google Cloud as its most immediate competitors. “Our competitive environment is very much dominated by the public cloud vendors,” CEO Frank Slootman told analysts. 

In summary: Snowflake is going after AWS, Microsoft, and Google Cloud. Those cloud leaders all want a piece of Oracle’s customer base. And Oracle, according to Ellison, is in a class of its own. For more on this, see my blog post “Can Oracle Beat AWS and Snowflake in the Cloud Database Wars?

Stalwarts and startups

Other vendors are refining their own competitive advantages. Teradata, once the epitome of an on-premises data warehouse vendor, recently announced availability of its cloud data analytics platform, Teradata Vantage, on Microsoft’s and Google Cloud’s marketplaces, added support for more data sources, and introduced a free cloud trial of Vantage. 

At the same time, cloud database startups are driving innovation with new products and business models. In January, Cockroach Labs announced it raised another $160 million in funding for its SQL database. Shortly thereafter, Databricks disclosed $1 billion in series G funding, with AWS, Microsoft, and Salesforce among the investors. 

Some cloud database startups have not yet earned their stripes in the enterprise, but that may just be a matter of time. Fauna, Firebolt, and Pinecone Systems are among the up-and-comers worth watching. 

THE PLATFORMS

Everything is a platform. The cloud database market has fully embraced this meme and with good reason—it’s what enterprise customers want and need. Teradata describes itself as a cloud data analytics platform. InterSystems is a cloud-first, next generation data platform. Splunk is the data-to-everything platform. 

The platform model one of the great advantages of the cloud. It’s much easier for vendors to assemble comprehensive database platforms using software-as-a-service tools and partnerships, and for customers to import data from disparate sources, run algorithms, distribute data across geos, and more. The Cloud Database Top 20 are heavily weighted toward such platforms.

Let’s look at Snowflake, which touts its ability to “eliminate data silos and run your workloads from a single platform.” Snowflake is a data warehouse, but it’s more than that. Snowflake’s architecture includes infrastructure capabilities such as storage and compute, pipelines to external data lakes, a marketplace where users can access hundreds of third-party data sets, and integration with machine learning tools and libraries. 

AWS CEO Andy Jassy said it's folklore to believe Amazon takes over industries
AWS CEO Andy Jassy

That is a bona fide cloud data platform, and there are others. CIOs and CTOs care about the full range of platform capabilities because it’s often the surrounding tools and services—things like data lakes and built-in machine learning—that account for the greatest business value. If data integration is fast and easy, if third-party analytics tools are a click away, if redundancy can be improved with multicloud capabilities, all of that results in less complexity and faster pay off. 

Purpose-built versus all-purpose

As the competition intensifies, a few battle lines have formed. One is SQL vs. NoSQL, which pits traditional relational databases against document databases and graph databases, for example. SQL, of course, is the widely used Structured Query Language.

But this is a fuzzy and even shifting line because NoSQL does not mean “no” SQL, as it seems to imply. Rather, NoSQL is short for “not only SQL.” Many NoSQL databases do in fact work with SQL queries. And a handful of the cloud database providers in our Top 20, including AWS, Google Cloud, IBM, Microsoft, and Oracle, offer both SQL and NoSQL options. Of the top 10 databases in DB-Engine’s database ranking (based on popularity), all support SQL or SQL-like queries.  

Another way to look at the cloud database decision has to do with the types of data and workloads to be managed. AWS, with 15+ databases in its portfolio, has thrown its weight behind the “purpose-built” model. Oracle, meanwhile, promotes its flagship system as a “converged” database that is well-suited for myriad data types and workloads. 

Here too, the line separating these two database styles is not sharp. Multimodel databases are something of a middle ground, capable of managing various data types, data models, and workloads, providing flexibility where needed. The database decision often comes down to the nature of the application supported and performance requirements. 

Google Cloud leans in the direction of purpose-build databases. For example, Google’s Cloud Bigtable excels at high-scale analytics and operational workloads, while Firestore is a NoSQL document database for new applications. 

“Most developers do not say, ‘I want one database for everything,’” Google Cloud director of product management for databases, Kelly Stirman, told me in a briefing for this report. A particular database may be ideal for one application, but not well suited for others, he said. “I don’t think you can engineer one database that serves all of them well.”

That said, Google’s Cloud SQL and Cloud Spanner databases are capable of handling a widening array of workloads in the same way multimodel databases do. 

Many IT organizations will not limit themselves to a single cloud database or cloud database provider but will use the best platforms for the job. We know that many companies already use several cloud service providers for SaaS, PaaS, or IaaS, and the same could happen with cloud databases. The trick is to avoid the complexity of that past that turned corporate data centers into spaghetti bowls of hardware and software. 

Key architecture components

An adaptable cloud database architecture is vitally important to reaping the benefits of the cloud database model without recreating the problems of the past. Here are key capabilities to consider:  

 

  • Hybrid. Few organizations are 100% cloud. The ability to connect existing, on-prem systems with the cloud database is a vital intersection point. This is IBM’s big play in the market with its RedHat stack. Other vendors, including AWS and Oracle, are expanding their hybrid cloud offerings. 
  • Multicloud. The ability to share data and connect databases across clouds is a practical requirement, and there are strategic benefits as well, such as being able to operate in the cloud of your customer’s choosing. Google with Anthos and MongoDB with multicloud clusters are among those promoting multicloud as a differentiating capability.  
  • Multimodel. Many cloud databases support multiple data types, but they do not all support the same data types. It’s important to assess strengths and weaknesses. 
  • Fully managed. Some cloud databases are self-managed by the user, some managed by the service provider, and a few such as Oracle Autonomous Database are fully automated. 

 

Data portability and applications compatibility hinge on having an adaptable architecture and the necessary tools. Virtually all of the cloud database providers offer data-migration tools and services to facilitate the shift of database workloads to their platforms. 

In December, AWS announced expanded options (for both source and target databases) for its AWS Database Migration Service, which has been used to migrate 350,000 databases to AWS. To spur migration to its platforms, AWS makes DMS available at no cost for six months to companies moving databases to Amazon Aurora, Amazon Redshift, Amazon DynamoDB, or Amazon DocumentDB. 

In November 2020, Google introduced a preview of its own Database Migration Service. When generally available, Google DMS will make it easier to move MySQL, PostgreSQL, and SQL Server workloads to Google’s Cloud SQL. Other vendors have similar tools.

A word of caution: Strategies around compatibility and interoperability are sometimes easier said than done. In one example, AWS says Amazon DocumentDB supports MongoDB 4.0 compatibility for the vast majority of the applications, drivers, and tools “with little or no change.” However, based on its own compatibility testing, MongoDB reports that Amazon DocumentDB 4.0 fails 63% of the MongoDB API correctness test.

Users will need to do their homework as they consider migrating to new cloud database platforms.

THE USERS AND USE CASES

Snowflake CEO Frank Slootman
Snowflake CEO Frank Slootman

There are several use cases that cloud database providers see as ripe for migration. They include application modernization, data governance (such as locating data in a specific country), and offloading mainframe or other legacy workloads to the cloud. But the starting point for many IT teams is new development. 

Developers are the most influential demographic in the database market and that includes cloud databases. Cloud database vendors are doing everything they can to win the hearts and minds of developers—events, online hubs, free-tier cloud services. 

Here’s a real-world example: As I was writing this report, I got an email from a cloud database vendor offering $300 in credits. “Activate your cluster by January 31, and an engineer will follow up to offer any help you need to get started,” it said. 

Vendors know that, if they can get developers interested in their platforms, it’s a foot in the door to the CTO’s or CIO’s office. That’s how they make the jump from being a point solution to part of an enterprise architecture.  

It’s revealing to see how cloud database vendors talk not just about their technologies, but the business value they deliver. As someone who has spent the past few years in strategic communications at several big database providers, I would say there’s room for improvement in how many of them do that. The conversation needs to be up-leveled from database vernacular—rows, columns, partitioning, JSON, multitenancy—to the language of business advantage.

 

Real-world solutions

User case studies are where the innovations, opportunities, and value are often revealed. Here are a few examples. 

  • Grab, the ride-hailing, food-delivery, and digital payments company in Singapore, is using Microsoft cloud services—Azure Synapse Analytics, Azure Data Lake Storage, and Azure Databricks—to experiment and create lightweight proof-of-concepts. The platform supports data sovereignty in eight countries and is used by data scientists and what they call data communities.
  • Flywheel, a WordPress hosting service, is using Google Cloud fully managed services to support 35,000 creative agencies and brands. Flywheel is using Cloud SQL, Google Kubernetes Engine, and Filestore for site performance and scale, and BigQuery for analysis.
  • JP Morgan Chase has undertaken a modernization effort that spans 35,000 developers, 6,000 applications, and 450 petabytes of data in a hybrid cloud environment. The financial firm is using Amazon’s ERM cloud platform for trading analytics, AWS Lambda and Amazon Elastic Kubernetes for risk calculations, Amazon Sage Maker for machine learning models, and Amazon Redshift to scale its analytic capabilities. 

 

Shared point of view

As these case studies show, the decision to deploy a cloud database often goes well beyond the database itself. It’s not uncommon for projects to weave together a half-dozen or more cloud services. This is a major advantage of cloud database platforms. 

The carrot that keeps these projects moving forward is greater business value. That can come in many forms: performance, scale, modernization, resiliency, governance, security, cost savings, customer relationships.

There’s tremendous opportunity. Businesses are generating terabytes, petabytes, and exabytes of data, but they require new ways to wring value from all of that data. Cloud databases can be a better way to aggregate, store, analyze, distribute, and drive insights and decisions with those data stores.

The Cloud Database Report is focused on how to move the needle toward modern, cloud-based data management. With our focus on the convergence of customer requirements, cloud innovation, and business value, the Cloud Database Report has a shared point of view with Cloud Wars, the leading source of analysis and insights on the cloud market. 

It’s a natural fit for the Cloud Database Report to be hosted on CloudWars.co, and I’m excited to be collaborating with my former colleague Bob Evans to bring fresh perspective and insights to the exciting world of cloud databases. Please join us as we report on this fast-changing market with an eye on what’s next.

Share your feedback, ideas, and tips with me at [email protected]

Snowflake CEO Frank Slootman
Snowflake CEO Frank Slootman

THE USERS AND USE CASES

There are several use cases that cloud database providers see as ripe for migration. They include application modernization, data governance (such as locating data in a specific country), and offloading mainframe or other legacy workloads to the cloud. But the starting point for many IT teams is new development. 

Developers are the most influential demographic in the database market and that includes cloud databases. Cloud database vendors are doing everything they can to win the hearts and minds of developers—events, online hubs, free-tier cloud services.

Here’s a real-world example: As I was writing this report, I got an email from a cloud database vendor offering $300 in credits. “Activate your cluster by January 31, and an engineer will follow up to offer any help you need to get started,” it said.

Vendors know that, if they can get developers interested in their platforms, it’s a foot in the door to the CTO’s or CIO’s office. That’s how they make the jump from being a point solution to part of an enterprise architecture.

It’s revealing to see how cloud database vendors talk not just about their technologies, but the business value they deliver. As someone who has spent the past few years in strategic communications at several big database providers, I would say there’s room for improvement in how many of them do that. The conversation needs to be up-leveled from database vernacular—rows, columns, partitioning, JSON, multitenancy—to the language of business advantage.

Real-world solutions

User case studies are where the innovations, opportunities, and value are often revealed. Here are a few examples. 

  • Grab, the ride-hailing, food-delivery, and digital payments company in Singapore, is using Microsoft cloud services—Azure Synapse Analytics, Azure Data Lake Storage, and Azure Databricks—to experiment and create lightweight proof-of-concepts. The platform supports data sovereignty in eight countries and is used by data scientists and what they call data communities.
  • Flywheel, a WordPress hosting service, is using Google Cloud fully managed services to support 35,000 creative agencies and brands. Flywheel is using Cloud SQL, Google Kubernetes Engine, and Filestore for site performance and scale, and BigQuery for analysis.
  • JP Morgan Chase has undertaken a modernization effort that spans 35,000 developers, 6,000 applications, and 450 petabytes of data in a hybrid cloud environment. The financial firm is using Amazon’s ERM cloud platform for trading analytics, AWS Lambda and Amazon Elastic Kubernetes for risk calculations, Amazon Sage Maker for machine learning models, and Amazon Redshift to scale its analytic capabilities. 

Shared point of view

As these case studies show, the decision to deploy a cloud database often goes well beyond the database itself. It’s not uncommon for projects to weave together a half-dozen or more cloud services. This is a major advantage of cloud database platforms. 

The carrot that keeps these projects moving forward is greater business value. That can come in many forms: performance, scale, modernization, resiliency, governance, security, cost savings, customer relationships.

There’s tremendous opportunity. Businesses are generating terabytes, petabytes, and exabytes of data, but they require new ways to wring value from all of that data. Cloud databases can be a better way to aggregate, store, analyze, distribute, and drive insights and decisions with those data stores.

The Cloud Database Report is focused on how to move the needle toward modern, cloud-based data management. With our focus on the convergence of customer requirements, cloud innovation, and business value, the Cloud Database Report has a shared point of view with Cloud Wars, the leading source of analysis and insights on the cloud market. 

It’s a natural fit for the Cloud Database Report to be hosted on CloudWars.co, and I’m excited to be collaborating with my former colleague Bob Evans to bring fresh perspective and insights to the exciting world of cloud databases. Please join us as we report on this fast-changing market with an eye on what’s next. 

 

Share your feedback, ideas, and tips with me at [email protected].

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About John Foley

I’m an independent writer and analyst covering the enterprise technology market with a focus on cloud computing and data management, and founding editor of the Cloud Database Report. As a tech journalist, earlier in my career, I covered databases and enterprise software, open systems, analytics, data centers, and all aspects of the emerging cloud market (SaaS/PaaS/IaaS). More recently, I established and led editorial teams driving strategic communications at Oracle, IBM, and MongoDB.

As a thought leader in the tech industry, I have traveled around the world meeting with CIOs and CEOs; written hundreds of blog posts and magazine articles on products, strategy, and implementation; explored innovative startups; and made countless trips to Redmond and Silicon Valley.

John Foley

About John Foley

John Foley

About John Foley

I’m an independent writer and analyst covering the enterprise technology market with a focus on cloud computing and data management, and founding editor of the Cloud Database Report. As a tech journalist, earlier in my career, I covered databases and enterprise software, open systems, analytics, data centers, and all aspects of the emerging cloud market (SaaS/PaaS/IaaS). More recently, I established and led editorial teams driving strategic communications at Oracle, IBM, and MongoDB.

As a thought leader in the tech industry, I have traveled around the world meeting with CIOs and CEOs; written hundreds of blog posts and magazine articles on products, strategy, and implementation; explored innovative startups; and made countless trips to Redmond and Silicon Valley.

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