Here's Who Made Gartner's 2019 Magic Quadrant For Data Management Solutions For Analytics

The Changing Data Management Landscape

The traditional approach to managing data for business intelligence applications is through the use of a relational database for analytics, perhaps as the foundation of a data warehouse system – likely on premise – with business analysis tools accessing the data through SQL or some other standard means.

But that model has been changing in recent years in several ways. Developers of next-generation NoSQL database systems like MarkLogic and Neo4j have been challenging database industry leaders such as Oracle and Microsoft. Cloud-service providers such as Amazon Web Services and Snowflake Computing, meanwhile, provide alternatives to building on-premises data warehouses and business analysis systems.

Which data management solutions for analytics (DMSA) vendors are leading the way in this industry transition? And who are the followers? Gartner’s 2019 Magic Quadrant for Data Management Solutions for Analytics gives us some clues.

Market Mega Trends

The DMSA market "continues to push toward distributed data management," notes the Gartner report, even amid a "resurgence of traditional relational data warehousing."

While cloud DMSA systems, such as AWS, and non-relational database technologies were once considered "disruptive" to traditional vendors, they have become more established components of the DMSA market while still battling established players.

Established vendors like Oracle, Microsoft and Teradata are "rediscovering" their core strengths and value propositions, according to Gartner, and leveraging their capabilities as a foundation for expanding into the cloud.

Niche players, meanwhile, are "doubling down on their core strengths" that differentiated them in the market and led to customer wins for best-of-breed use cases.

DMSA Magic Quadrant Methodology

Vendor positioning in the magic quadrant is determined by their ability to execute and their completeness of vision.

Ability to execute is primarily concerned with vendors' capabilities and maturity, Gartner said, as well as their products' portability and ability to scale and run in different operating environments. Vendors were evaluated according to their product or service, their overall viability, sales execution and pricing, marketing responsiveness and execution, and customer experience.

The criteria for completeness of vision assessed a vendor's ability to understand the functional capabilities needed to support DMSA environments, Gartner said, and their ability to develop a product strategy that meets market requirements and trends. Vendors were evaluated according to their product strategy, marketing and sales strategies, market understanding, geographic and vertical industry strategies, business model and ability to innovate.

Leader: Oracle

Oracle is one of eight vendors in the Leaders quadrant, by far the highest along the "Ability to Execute" axis of any vendor and just ahead of Teradata and Microsoft on the "Completeness of Vision" axis. The company develops a range of data management products including its flagship Oracle Database 18c and the Oracle Big Data Management System, as well as cloud offerings like the Oracle Database Cloud Service and Oracle Autonomous Data Warehouse Cloud.

Strengths: Oracle received the highest score for product capabilities from reference customers – no surprise given that the Oracle database has long been one of the industry's leading database products. Oracle's Autonomous Data Warehouse also received high marks and the company scored well for availability of third-party resources and ease of deployment and integration.

Cautions: Oracle's pricing and licensing practices "continue to be poorly thought of" by customers, according to Gartner, although customer reference scores in pricing and licensing did improve over the prior year. The company has a "historical lack of small enterprise and developer outreach" and was relatively late to the cloud compared to competitors like AWS, Google and Microsoft.

Leader: Microsoft

Microsoft's data management product lineup is focused on its SQL Server database and a number of cloud offerings based on its Azure cloud platform including the Azure SQL Data Warehouse, the Hadoop-based Azure HDInsight, the Spark-based Azure Databricks analytics platform and Azure Data Lake.

Strengths: Microsoft's Azure-based products provide a comprehensive logical data warehouse vision and capabilities for distributed processing environments, according to Gartner. Microsoft grew at twice the rate of the overall DBMS market in 2017 and the market research firm gives the company high marks for market execution and cloud focus. Microsoft also scores high in customer loyalty.

Cautions: Some customers report performance issues with the first generation of the Azure SQL Data Warehouse, according to Gartner, but the second generation of the technology offers improved performance. Microsoft received below average scores for "value for money" and average scores for pricing flexibility. And some products have product functionality and maturity issues.

Leader: Amazon Web Services

AWS' core entry in the DMSA space is its Amazon Redshift data warehouse service in the cloud. Other services include Amazon S3 cloud object storage, AWS Lake Formation data lake, AWS Glue data integration and metadata catalog, Amazon Elasticsearch search engine, Amazon Kinesis streaming data analytics, Amazon QuickSight business intelligence visualization and more.

Strengths: AWS is widely considered the leader in cloud data management services, providing a broad range of supporting services, a pool of third-party resources and a huge customer base for AWS DMSA services, according to Gartner. AWS accounted for more than 40 percent of the growth in the entire DBMS market in 2017, giving the vendor financial clout and stability. And AWS has begun developing an on-premises presence with its Relational Database Services on VMware and AWS Outposts products.

Cautions: Integrating AWS' various services for different use cases can be complex, according to Gartner. Customer scores for value for money were in the bottom quartile of vendors in the Magic Quadrant and in the bottom half for pricing and contract flexibility. And while customer scores for AWS product capabilities were average or better, they were one of the lowest average scores among the vendors covered in the report.

Leader: Teradata

Data warehouse pioneer Teradata was second only to Oracle in "completeness of vision" in the leader quadrant, but behind Oracle, Microsoft, AWS and SAP in "ability to execute." The company offers the IntelliFlex and IntelliBase data warehouse appliances, a software-only package with a SQL engine and machine learning, and the IntelliCloud cloud service through public cloud services. In October Teradata announced the new Vantage packaging and branding for its analytics platform.

Strengths: Teradata has always been seen as a best-of-breed option for data warehousing with customer scores in the top third of vendors for product capabilities, service and support, and system availability. Customer scores were near the top of all vendors for the ability of the company's technology to handle large, complex workloads. And Teradata has been simplifying its product portfolio and branding.

Cautions: Teradata has been focused more on the high end of the market and that has limited its growth in broader markets, according to Gartner. The general market perception is that Teradata is not a cloud vendor despite its multi-cloud and rebranding strategy. The company received below average scores from customers for overall experience, pricing and contract flexibility and, for the second year, below average scores for customer satisfaction and account management.

Leader: SAP

The SAP data management portfolio includes the HANA in-memory, column-store database management system, supporting operational and analytical tasks, and the SAP BW/4HANA data warehouse system. Both are provided as on-premises and cloud solutions. Also offered are the Hadoop-based SAP Cloud Platform Big Data Services and SAP Vora for Spark and Hadoop processing.

Strengths: SAP has pursued a multi-cloud strategy, supporting AWS, Google and Microsoft Azure, and aggressively demonstrated a strong focus on artificial intelligence and machine learning capabilities. Customers give high praise to SAP HANA's performance and scalability.

Cautions: Some reference customers consider SAP's DMSA products to be expensive and give below average scores to the company for technical support. Gartner also says that while SAP has expanded its cloud partnerships and product lineup, the cloud technology's compute capabilities cannot be elastically increased or reduced dynamically over short timescales.

Leader: Snowflake Computing

Fast-growing Snowflake offers fully managed cloud data warehouse services running on either AWS or Microsoft Azure with a number of advanced capabilities including ACID-compliant relational processing, a native Apache Spark connector, R integration, dynamic elasticity and data-sharing capabilities.

Strengths: Customer references give Snowflake high marks for customer experience, value for money, pricing and contract flexibility, product capabilities and ease of deployment, according to Gartner. Its architecture provides dynamic elasticity for effective scalability and customers praise the service's operational efficiency.

Cautions: Snowflake's services have been available for less than four years and lack some key features. But that list included materialized views, which just recently became available, and stored procedures, which are currently in preview. Gartner notes that the company's hypergrowth creates the challenge of maintaining a high level of customer engagement, particularly in customer training resources and support.

Leader: Google

Google's database Platform-as-a-Service offerings include the BigQuery managed data warehouse services, Cloud Dataproc managed Spark and Hadoop services, and Cloud Dataflow batch and stream data processing.

Strengths: Customers give high marks to the performance and ease of use of Google's products. The Gartner report said Big Query is capable of addressing a wide range of use cases through its use of machine learning. And Google Cloud, in general, is gaining market traction.

Cautions: Gartner said many offerings in the Google Cloud Platform were originally designed to support the company's consumer business: While the platform services have matured to better support enterprises, Google is still ramping up its go-to-market support. System management and administration can be an issue, Gartner said, and some customers complained about cost predictability.

Leader: IBM

IBM serves up a broad range of data management products and services including the Db2 line of database software, the PureData System analytics appliances, the Db2 Warehouse on Cloud managed data warehouse cloud services, the BigInsights Hadoop solution, and Db2 Event Store data management for IoT and time series data.

Strengths: IBM gets high marks in the Gartner report for its broad and diverse DMSA product portfolio. Specific technology strengths include integration for the Db2 Analytics Accelerator for data residing on mainframes and the rich SQL functionality for Hadoop in the Big SQL product.

Cautions: IBM had the lowest position on the "ability to execute" axis among all the companies in the Leaders quadrant. Gartner said IBM faces a challenge as it phases out its PureData System for Analytics in favor of the Db2-based Integrated Analytics System appliance. Customers reported "suboptimal" support experiences and Gartner said some newer products require software fixes and improvements.

Visionary: MarkLogic

MarkLogic has developed a non-relational, multi-modal database management system that can be deployed on-premise, in the cloud or in hybrid environments. The company also offers Data Hub software for integrating data on-premises or as a cloud service.

Strengths: MarkLogic is the only company in the Visionaries quadrant in this Gartner report and the company is further along the "Completeness of Vision" axis than some of the companies in the Leaders quadrant. Gartner cites the company's "strong and unique vision" for integrating data across multiple data platforms and data types and gives high marks to its technical and enterprise capabilities. MarkLogic also utilizes an innovative cloud pricing model, according to Gartner.

Cautions: MarkLogic's biggest problem is low mind-share in a crowded market. Revenue growth is slow and sales execution needs a boost, according to Gartner, while the vendor also needs to improve the ease of deployment of its products and increase the availability of third-party resources.

Niche Player: Cloudera

Cloudera develops a big data software platform for data engineering, data warehousing, machine learning and artificial intelligence tasks. The company's flagship product is the Cloudera Enterprise platform with versions offered for data warehousing, data integration, and data science and engineering. In early January Cloudera merged with rival Hortonworks, which was positioned just below Cloudera in the Niche Players quadrant.

Strengths: Cloudera has maintained sustained growth above the overall database market. The company has made a strong push to support data science, machine learning and AI use cases. And customers scored the company high on the quality of its training resources.

Cautions: Cloudera faces increased competition from suppliers of cloud-native data management services, according to Gartner, and the company must improve the performance of its Impala massively parallel processing SQL query engine. But perhaps the biggest challenge is making its merger with Hortonworks work, including rationalizing and integrating the two vendors' product lines, and getting past the almost inevitable customer uncertainty.

Niche Player: Huawei

Chinese networking giant Huawei markets the FusionInsight Big Data platform, combining Apache Hadoop, Spark and Storm with the proprietary FusionInsight GaussDB 200 proprietary MPP database.

Strengths: Huawei is strong in its traditional telecommunications vertical, especially in China, and Gartner gives the company high marks for its financial strength and stability. The Gartner report also said Huawei benefits from strong customer loyalty and satisfaction.

Cautions: There is limited awareness of Huawei's DMSA offerings outside Asia/Pacific and much of its success is limited to the core telecommunications vertical. Gartner also said Huawei received among the highest number of customer complaints about its ability to support complex implementations, possibility related to complex use cases rather than product capabilities, Gartner said.

Niche Player: Micro Focus

U.K.-based Micro Focus markets the Vertica Enterprise analytics platform based on a columnar relational database sold as a software-only solution for on-premises use and as Vertica in the Clouds from AWS, Microsoft Azure and Google Cloud Platform.

Strengths: The Micro Focus software gets high marks for its in-database analytics, machine learning and data science capabilities, and for its scalability and performance, according to Gartner. Customers also praise the vendor for overall experience, service and support, and value for money.

Cautions: The Vertica product has suffered from declining mind share and market share, Gartner said, and Micro Focus was slow to move to the cloud, offering Vertica in an Infrastructure-as-a-Service form factor with no database Platform-as-a-Service offering. Customers also say Vertica requires a significant maintenance and administration effort during initial implementation.

Niche Player: Pivotal

Pivotal's flagship product is the Pivotal Greenplum open-source MPP database based on PostgreSQL technology. The product is available as software and a cloud service, as well as a database appliance through a Dell partnership.

Strengths: Customers give high scores to the overall performance and scalability of Pivotal Greenplum and say it has robust in-database analytics capabilities, Gartner said. Pivotal Greenplum is also strong in Asia/pacific markets, most notably China.

Cautions: Pivotal Greenplum's cloud offerings lack maturity and enterprise readiness, according to reference customers. The Greenplum technology requires deep technical skills to provide value, and there are challenges with managing complex, mixed workloads.

Niche Player: ARM (Treasure Data)

ARM Treasure Data markets a customer data platform running on AWS infrastructure that includes a dully managed DMSA, data lake and relational data marts.

Strengths: Treasure Data was acquired in 2018 by Arm Holdings, part of SoftBank Group, bringing financial strength and stability to the company. The company has deep expertise in several vertical industries including retail and consumer packaged goods, according to the Gartner report, and in IoT. The company also generates solid customer satisfaction scores in such areas as support and ease of deployment.

Cautions: The company's product is complex and can be difficult to manage and troubleshoot, Gartner concludes, with some customers saying the technology can be expensive to scale.

Niche Player: GBase

GBase (Beijing-based Tianjin Nanda General Data Technology) has developed a relational MPP data warehouse system, the GBase UP logical data warehouse (LDW) platform, the GBase Infinidata 8a data warehouse appliance and the GBase HD Hadoop distribution.

Strengths: Gartner gives high marks to the GBase UP system's MPP relational technology combined with exploratory use cases based on Hadoop infrastructure. Customers appear quite loyal to the company and praise its pricing and contract flexibility.

Cautions: Gbase has limited global presence with 85 percent of its deployments in Asia/Pacific and most of that in China. The vendor has limited cloud offerings and customers said its documentation isn't always up to date on new releases and features.

Niche Player: MapR Technologies

MapR's converged data platform includes the MapR-DB non-relational database with support for key value, document, wide-column, graph and time-series data; MapR-XD POSIX-compliant data storage; event-streaming capabilities and Network File System. The company's small-footprint MapR Edge targets edge-processing applications such as IoT.

Strengths: Gartner says MapR provides the only Hadoop-compatible alternative to Cloudera, following that company's merger with Hortonworks, and MapR has an opportunity to recruit Cloudera and Hortonworks customers concerned about merger-generated uncertainty. MapR is in the top quartile of vendors in customer loyalty and the company gets high scores for overall customer experience, as well as evaluation and customer negotiation.

Cautions: Once Cloudera fully integrates Hortonworks the company will dominate the Hadoop space. Some reference customers said deploying and integrating the MapR platform can be a challenge. And the company faces increasing competition from cloud-native alternatives.

Niche Player: Alibaba Cloud

The cloud computing division of the giant Chinese conglomerate Alibaba Group Holding offers a wide range of database services including ApsaraDB relational database service, HybridDB based on the Pivotal Greenplum Database, MaxCompute for large data warehouse implementations and E-MapReduce for Hadoop.

Strengths: Alibaba Cloud has a "broad and deep" DMSA product portfolio and, like Amazon Web Services, is backed by the financial strength of its parent company. The company also benefits from Alibaba's strong presence in China and Asia/Pacific.

Cautions: Alibaba Cloud had the lowest "completeness of vision" positioning among all vendors covered by the Gartner report. Gartner said it can be difficult for potential customers to navigate its "confusing product portfolio" and the quality of its documentation is uneven. Alibaba could also be hurt by the current geopolitical environment in North America and U.S.-China trade tensions.

Neo4j

Neo4j has developed a graph platform that includes the Neo4j native graph database, graph analytics, graph visualization and the Cypher graph query language. The company offers Enterprise, Desktop and Community editions of its software.

Strengths: Neo4j is generally seen as the leader in graph database technology, which uses graph structures to represent and store data. The company scores high from customers on "value for the money" and the quality of its service and support.

Cautions: Neo4j held the lowest position on the "ability to execute" axis among all vendors covered in the report. Gartner says Neo4j is not suitable for all DMSA use cases and the market researcher said the company's technology "scored poorly with its reference customers for overall system availability." And customers report using the product for relatively small datasets of less than a terabyte.