I recently collaborated with my colleague Sanjeev Mohan on our first joint written piece since leaving Gartner. We picked a favorite topic – Database Management Systems. These are our views, and should not be construed as Gartner’s position.

Gartner’s 2023 Magic Quadrant for Cloud Database Management Systems, published in December 2023 based on vendor evaluations from June, marks Gartner’s 28th annual DBMS Magic Quadrant. Critical Capabilities reports for one Operational DBMS and one Analytical DBMS product from each vendor published in January 2024. 

Gartner expects DBMS market size to have crossed the $100B mark for 2023 when it publishes numbers. Growth is primarily in the cloud, and the hyperscalers are extending the revenue gap. Our estimate is that AWS alone, with RDS ($7B ARR) and Aurora ($4B ARR) among many other offerings, now commands over 10% of the global database market. 

2023 was clearly a year of change for the market, with significant shifts for well over half the vendors included–mostly “down and to the left” compared to 2022. Gartner evidently sees the market entering a new stage, though as we note below, its description of market factors has not changed much. 

However, one key prediction is that “by 2027, 75% of DBMS purchases will be made by line-of-business domain leaders, up from 55% in 2022.” The implications are striking – increasingly purchase decisions will not be made by technology experts.

Report highlights

The 51-page MQ describes significant changes throughout:

• A changing landscape: of 19 listed vendors, 17 were in the 2022 report. EDB and Yugabyte were added. Three were dropped into Honorable Mentions, which do not appear in the graphic. Aiven, Clickhouse, Huawei Cloud, OceanBase, OpenText, PingCap, SingleStore were new, while MarkLogic (now Progress), Tencent Cloud and TigerGraph dropped from the previous year. 
• Shifting placement: 11 vendors saw their positions move downward (the Execution axis), while Alibaba, CockroachDB and Intersytems moved up. Left to right movement (the Vision axis) was a roughly even split.  
• The hyperscalers (AWS, Microsoft and Google) remained at the top: though Google saw a slight decline in its position, it moved to the right, emerging with the leading vision placement.
• Four vendors dropped out of the Leaders Quadrant: Cloudera, IBM, SAP, and Teradata, a rare and significant change.
• Several vendors moved significantly to the right: Neo4j is now in the Visionary quadrant, while Alibaba, Databricks, and MongoDB improved as well.
• Leading Critical Capabilities product scores were no guarantee of continued Magic Quadrant positioning at the top: Most vendors rated comfortably ahead of the “Meets Requirements” line in Gartner ratings – but doing so is not enough to lead the market. 

The readers who make their way to page 45 of the full MQ document are rewarded with a few pages of analysis. In this post, we’ll examine that and offer our own thoughts about Gartner’s view of the market.

Caveats

Even consumers accustomed to the MQ for many years often forget that the MQ analyzes companies, not products. The accompanying Critical Capabilities reports each analyze one product. But Product is only one of seven MQ Execution Criteria in the; Product Strategy is one of eight Vision Criteria.

Being a Leader may be the holy grail for vendors, but buyers should recognize that your specific business and technical requirements may be better served by a DBMS from a vendor in one of the other three categories – Niche, Visionary, and Challenger.

In addition, the sheer size of all these reports results in a very low readership of the full report. Too many readers only look at the graphic and miss out on all the rich details in the document. 

Overview

This year’s MQ continues the recent trend of later and later publication, appearing just before the end of the year; the Critical Capabilities slipped into January 2024. This lags market developments—the data used, as the basis of the assessments predated the generative AI frenzy that gripped the market in the second half of the year. 

Last year, 12 companies crowded the Leader quadrant. They were so closely clustered that it was hard to tell one from another. This year the distribution is more spread out (in alphabetical order):

●  Leaders (8): Alibaba, AWS, Databricks, Google, Microsoft, MongoDB, Oracle, Snowflake

●  Challengers (1): Intersystems

●  Visionaries (6): Cloudera, IBM, Neo4j, Redis, SAP, Teradata ●  Niche (4): Cockroach Labs, Couchbase, EDB, Yugabyte

Figure 1: Gartner 2023 Cloud Database Management System Magic Quadrant (CDBMS)

Niche Players

Let’s start with the newbies – EDB and Yugabyte. First of all, congratulations to the vendors, who are now among the top 19 vendors Gartner chose to analyze (inclusion criteria are discussed below.) Being in the niche category should not be considered a negative – it is a typical point of entry, and suggests the vendor has a distinct,differentiated position that may be a base from which to improve (or maintain) their position. 

EDB has carved out a reputation as a leader in PostgreSQL, with strong community support. Gartner points out that it took EDB a while to get its footing in the cloud and that it faces significant competition as more vendors promote their own PostgreSQL offerings. Yugabyte is Postgres-compatible and has carved out leadership among the growing set of vendors targeting distributed DBMS, and like EDB it faces growing competition.

One of EDB’s competitors is CockroachDB, also distributed, and also Postgres-based. In the Critical Capabilities for Operational Use Cases report, the two vendors have very similar ratings: CockroachDB has a slight lead for Lightweight Transactions, Yugabyte a lead for Operational Intelligence – and for OLTP the two are separated only by a statistically insignificant .01 on a scale of 5. The narrowness of this gap highlights the reason for our first key takeaway:

The reports are the beginning, not the end, of your evaluation. Dig deep, and talk to an analyst to map to your requirements.

The other vendor in this quadrant, Couchbase, has distinguished itself over the years by its strong support for mobile (today, we might call them edge) use cases and strong JSON support. Despite its size disadvantage relative to the largest vendors, Couchbase has a defensible differentiation and should be able to continue to do well as other players in the market focus on other trends. 

Challengers

Intersystems stands alone in this category, moving up significantly in execution from 2022, when it was a Visionary. A slight shift to the left, just enough to move it across the center line, was in keeping with the general trend – and is not unusual in a vendor journey over the years as a leading vision is consolidated in a focus on execution. Gartner notes the vendor’s increasing success in financial services and supply chain, from its strong base in healthcare. The product ratings in the Critical Capabilities reports are solid, middle of the pack results well above the Meets Requirements line.

Visionaries

It’s interesting to note that the sole Challenger from 2022 also moved from one quadrant to another. Redis moved into the Visionary quadrant, getting credit for its expansive portfolio of tools for many different use cases. Its headwinds are clearly shifting as other vendors target its open source basis with offerings of their own, potentially slowing its footprint expansion. It is not included in the Critical Capabilities report for Analytics at all,which pulls a vendor down on the MQ.

Neo4j, on the other hand, was the only vendor to move into the Visionaries quadrant from the left in 2023. Its continuing leadership in Graph DBMS, and its preparedness and vision for that category’s obvious value to AI and especially Generative AI use cases,clearly helped. Gartner highlighted customer satisfaction, and the company’s stability as TigerGraph struggled with executive turnover suggests 2024 will be a good year even as competition heats up.

Cloudera, IBM, SAP and Teradata are the remaining Visionaries, and they have one thing in common – all dropped out of the Leaders quadrant in 2023. This is unprecedented.

In IBM’s case, a multiyear decline in market share, including a year or two where revenue dropped, continued in 2023. Despite its product leadership – Db2 Warehouse was in the top 5 in the Analytical Critical Capabilities use cases, and only slightly lower in the Operational report – its market momentum clearly did not impress Gartner. 2024 may be a better year – IBM seems to have taken GenAI seriously and its pricing for users of LLMs is already getting favorable comments from market observers.

Teradata offers a stark illustration that product leadership is not enough. It leads for Logical Data Warehouse and is tied for first with Oracle for Traditional Data Warehouse in the Analytical Critical Capabilities report. For Data Lake, it was in fourth place (the surprise here being AWS Redshift is in third place.) Nonetheless, its market performance clearly did not impress Gartner – and it does not help that it is not included in the Operational Critical Capabilities report. It was Teradata’s choice in previous years not to participate in that report because it does not target those use cases. Slipping revenue, executive turnover, and the gutting of its analyst relations team obviously did not help.

In SAP’s case, its drop comes at the end of a long effort to substantially broaden the user base for its DBMS beyond the users of its applications – an effort that has not succeeded. Product strength again proves to be insufficient – SAP HANA Cloud is in the top 5 for all the Operational use cases and two of the three Analytical ones.

Finally, Cloudera delivered solid Analytic ratings, but continues to lag on Operational ones. It bucked the overall leftward drift in Vision owing to its strength in multicloud hybrid delivery and governed AI capabilities, but its marketplace performance in 2023 as it transitioned its executive team was evidently not enough for Gartner to keep it among the leaders.

Collectively, these results illustrate our second key takeaway:

The MQ is about Gartner’s view of a company’s marketplace performance. Product leadership is not enough. 

Leaders

Finally, the Leaders quadrant: a dramatic drop from 12 vendors to 8 shows a market continuing to winnow out former stars as the cloud remakes the landscape. The market’s leftward drift is very visible here in the top cluster, who retained their distance from the rest of the market in execution. AWS, Microsoft and Oracle all moved to the left – Google bucked the trend and moved slightly to the right, taking the vision leadership. Oracle, whose DBMS revenue in the cloud has continued to grow much less slowly than the others, fell vertically as well.

Alibaba bucked the overall downward trend, moving up and to the right this year as Gartner noted its increased product development and delivery and its growing ecosystem involvement. 

Databricks moved up slightly, and was praised for its data science roots and Unity Catalog. Its placement as a Leader despite its absence from the Operational Critical Capabilities report reflects its robust performance.

MongoDB moved to the right as it grew beyond its documents-first message despite growing competition, sustaining its strong hybrid multicloud marketplace execution. Its rightward move in vision placement likely reflects its attention to adding analytics. These were not assessed; presumably the 2024 Critical Capabilities will include those as they are delivered to the market.

Snowflake dropped somewhat, although Gartner acknowledged its continuing rapid growth. Gartner called out time to delivery of announced features and the absence of on-premises support as factors in the ratings.

Overall, the Leaders quadrant shows that Gartner’s long-standing assertion that the hyperscalers would continue to distance themselves is proving out. The report notes that vendors of cloud DBMS more consciously seek to interoperate with surrounding data management components. In the case of the hyperscalers’ portfolios, this effect is magnified by the fact that their portfolios contain products in those categories which may be easier to integrate than third-party products, require fewer points of contact for support, and may have cost advantages. 

Vendors DroppedFrom Graphic in 2023

Three vendors were dropped this year.

MarkLogic (acquired by Progress in February 2023) has not yet seen marketplace benefits. Progress itself has not appeared in a Magic Quadrant for years – its focus was not on DBMS sales to end users.

TenCent Cloud has not made market share inroads in Gartner assessments of the global cloud marketplace, and this is reflected in the DBMS’ positioning as well. (By contrast, Alibaba actually improved its DBMS MQ position even though it also lost share as a cloud platform.)

TigerGraph ran into financial trouble in 2022 and shuffled its China-based leadership suite. It brought a new release to market that incorporates support for OpenCypher, the open source graph query language championed by Neo4j.

Inclusion Criteria – Who Qualifies and Why?

DBMS vendors want to be in the MQ; its value for marketing and sales organizations is considerable. Although the stubborn rumor of the MQ being “pay-for”play” refuses to go away, as ex-Gartner analysts we can categorically refute any such insinuations. Gartner analysts’ assessments are completely independent of any account-related considerations. The analysts analyze evidence submitted by the selected vendors along with Gartner’s substantial body of primary research and end user inquiries. The onus is on the vendors to ensure they have clearly conveyed their strengths; the effort required to respond to Gartner’s Requests For Information is considerable.

Inclusion in the Magic Quadrant is limited because the mechanics of the graphic display and screen real estate impose a practical limit. In the past, a threshold of annual revenue was one component, but that was removed some years ago in order to let smaller vendors participate. The criteria for vendors with a product generally available as of July 1, 2023 included:

• Functional capabilities including transactional and/or analytic capabilities and managing data on cloud storage as well as their own data persistence capability.
• Support for the needs of a set of use cases defined by Gartner, whose requirements drive the weighted Criteria in the product-specific Critical Capabilities research documents that accompany the MQ.
• Geographic market presence in 3 regions defined by Gartner.
• Ranking in Gartner’s Customer Interest Indicator (CII), an algorithm which uses inquiry to Gartner, mentions in Gartner Peer Insights (a publicly available ranking service), and publicly available data including press mentions, job listings, and others.

This inclusion model is based on definitions of the DBMS market that date back decades and have evolved slowly over the years, lagging shifts in the nature of product offerings and buying patterns. Research that is published every year tends to be constrained by the need for longitudinal comparability – that is, the ability to compare over time to spot trends. As markets shift and product portfolios take different shapes, this constrains the model.

One example of these challenges is technology-based. Products evolve, and definitions must keep up. For example, Gartner combined Operational and Analytic DBMS MQs years ago because almost all  vendors offered both capabilities in a single product. Gartner publishes two specialized Critical Capabilities reports addressing those use cases, because a vendor portfolio may contain multiple products to target those needs. Similarly, as the focus of buyers moved to the cloud, Gartner opted several years ago to make support for cloud operation a requirement. 

Another challenge is driven by changes in the buyers’ expectations of the products’ capabilities. Over the years, both buyers and sellers drove expansion in the products’ footprint to include data integration, data pipelines, built-in analytics, machine learning, metadata management, data quality and many more features that also existed as separate products – from different vendors as well as the same vendors who sold the DBMS. These changes are partially accounted for in Gartner’s evolving  product definitions in the research, but not entirely. Several of the categories in the list above have their own Magic Quadrants, written by different analysts, whose definitions of their markets may include or exclude some of the vendors in the Cloud DBMS MQ, even if they also offer those capabilities as part of their CDBMS product.  

Perhaps most challenging is the scope of the research as defined by Gartner’s market taxonomy and the limitations of the documents. Gartner’s Cloud DBMS Critical Capabilities reports only assess a single product from each vendor. By creating two reports that number is doubled. But AWS and Google, for example, have many more unevaluated DBMS products. These may be covered by the analysts who write the MQ and Critical Capabilities reports, but are not included in the data collection done by RFI submissions from the vendors. Thus, our third key takeaway:

Gartner’s Magic Quadrant and Critical Capabilities reports provide incomplete assessments of the full Cloud DBMS portfolios of any vendor with over two products in the market, and do not assess the synergies across those portfolios.

Gartner’s View of the Market

Gartner’s Market Overview, on pages 46-48 of the MQ, is descriptive. It notes that the continuing growth of the entire category,is above the overall software market’s growth, and is itself increasingly driven by its cloud component (55% of DBMS revenue in 2022). Market driver, include:

1. Increasing “data ecosystem” support – that is, interaction with surrounding data management technology from the same vendor and others. (Other market observers discuss the notion of the “modern data stack” in a similar fashion.)
2. Low-code/no code capabilities, associated for some reason here only with Analytical DBMS. It’s not clear whether, or why, these were not also considered for Operational uses.  
3. Distributed transaction and remote database capabilities. Pioneering vendors like Yugabyte and CockroachDB face increasing competition here.
4. Support for machine learning and model training, monitoring and operation.
5. Financial governance, where Gartner’s research has provided thought leadership and helped to frame the FinOps discussion.
6. Open source interfaces, with a nod to PostgreSQL and MySQL.

This is familiar stuff. It says little to assess the impact of the rise and adoption of: 

• Nonrelational technologies – by users and their inclusion into vendor portfolios
• The emergence and importance of vector databases, LLMs and retrieval assisted augmentation for generative AI
• Increased use of new processor types and a variety of memory technologies 
• New storage layers in the cloud including hyperscaler-optimized stores in their platforms, and table formats such as Delta Lake and Apache Iceberg. 

Vendors are prioritizing these issues to varying degrees, and Gartner’s assessment of their roadmaps and how those align with Gartner’s own expectations about market development are not mentioned. It may be a year before such questions are answered when the Magic Quadrant and Critical Capabilities reports for 2024 are published. Given how much impact these issues will have on both expectations and results, we are likely to see more movement of the dots.