Here's Who Made Gartner's 2016 Magic Quadrant For Data Warehouse And Data Management Solutions For Analytics
Data Solutions Are In Demand
Customer demand for broad data solutions addressing multiple types of data -- and offering distributed processing and repository options -- is accelerating disruption in the market.
Organizations want to manage and process internal and external data of diverse types and in diverse formats along with the data they acquire from traditional internal sources.
"This requirement is placing new demands on software in this market as customers are looking for features and functions that represent a significant augmentation of existing enterprise data warehouse strategies," Gartner noted.
Gartner's latest Magic Quadrant for Data Warehouse and Data Management Solutions for Analytics, released near the end of February, rates 21 vendors jockeying for position in a hot and rapidly evolving IT sector. Here's how they stack up.
Methodology
Gartner defines a data warehouse or data management solution as a complete software system that supports and manages data in one or many file management systems -- most commonly, databases. They can perform relational processing, even if data is not stored in a relational structure, and enable access and data availability from independent analytical tools and interfaces.
The Gartner Magic Quadrant ranks them on two criteria: Ability to Execute and Completeness of Vision.
Execution is represented on the Y-axis of Gartner's chart, and vision on the X-axis. That lands competitors into one of four quadrants on the chart: Niche Players (low in both criteria), Visionaries (complete vision but lacking execution), Challengers (good execution but lacking vision), and Leaders (excelling in both vision and execution).
Challenger: 1010data
Product: Managed service data warehousing.
1010data's integrated DBMS and business intelligence solution is aimed at the financial services, retail/consumer packaged goods, telecom, government and health-care sectors.
1010data
Strengths: The New York-based company's growing at a good clip and now has more than 750 clients. It's benefited from lessening concerns around governance, and clients praise the ease of use for interactive analysis, data loading and analytical capabilities. Media giant Advance acquired the company in August 2015, exposing 1010data to a new source of funding for development projects.
Cautions: 1010data focuses mainly on supporting analytical needs for data managed in its own cloud. And it's presence outside the U.S. is small.
Niche Player: Actian
Product: The Actian Analytics Platform for data warehouse and data management solutions is composed of three products:
Matrix, a massively parallel processing (MPP) DBMS engine.
Vortex for analytics on Hadoop.
Vector, a symmetric multiprocessing (SMP) analytics DBMS.
Actian
Strengths: Palo Alto, Calif.-based Actian's integrated platform supports all major use cases for data warehouses and data management solutions for analytics (DMSAs). Vortex offers integration capabilities paired with analytical capabilities on top of Hadoop. Customers praise the query performance and ability to support analytics.
Cautions: ParAccel, the product that became Matrix, formed the basis of Amazon Redshift. But the technologies have since evolved independently, and Actian customers can't combine them for hybrid cloud deployments. Matrix is available as a cloud service with third-party providers like Microsoft Azure and Rackspace.
Gartner has concerns about Actian's visibility in the market, and customers have mentioned the product's lack of completeness as an issue.
Challenger: Amazon Web Services
Products: Amazon Redshift, a data warehouse service in the cloud.
AWS Kinesis for streaming data.
Amazon Simple Storage Service (S3) and Amazon Elastic MapReduce (EMR).
Amazon Web Services
Strengths: AWS, Seattle, is often considered the leading cloud data warehouse Platform-as-a-Service provider, and the platform is gaining adoption, driven by its ability to deliver both technical and financial flexibility and agility.
Amazon's cloud supports many use cases when data management solutions are combined. Customers tell Gartner they plan to invest more in Redshift, demonstrating their satisfaction.
Cautions: AWS has a big target on it its back.
"All the major vendors -- IBM, Microsoft, Oracle, SAP and Teradata -- are now actively competing with AWS in the cloud with varying degrees of support for true data warehouse platforms as a service," Gartner noted.
Competition on pricing and functionality means more options for customers, and the need for more scrutiny to truly compare those offerings.
Because AWS is a pure-play cloud vendor, Redshift lacks support for hybrid data warehousing combinations that Gartner predicts will be the norm by the end of 2018.
Visionaries: Cloudera
Product: A data storage and processing platform based on the Apache Hadoop ecosystem, with a proprietary system and data management tools for design, deployment, operation and production management.
Cloudera
Strengths: Palo Alto, Calif.-based Cloudera differentiates itself from other Hadoop vendors by continuing to invest in unique capabilities, such as further improvements to Cloudera Navigator, which provides metadata management, lineage and auditing.
Cloudera's positioned itself to complement traditional data warehouse and made use of its relationships with traditional DBMS vendors, particularly Oracle.
Cautions: Cloudera mainly addresses the cloud using an Infrastructure-as-a-Service approach that does not offer scalable, elastic and managed service support, Gartner says.
The vendor has expanded into new geographies and added clients, leading some customers to feel the availability of support or professional service resources has become constrained.
Niche Player: Exasol
Product: An in-memory column-store DBMS, available as a free single-node edition, a clustered solution and a Dell appliance.
The DBMS is also offered as a fully managed solution on ExaCloud and from third-party cloud service providers such as AWS, Microsoft Azure and Rackspace.
Niche Player: Exasol
Strengths: Exasol, Nuremburg, Germany, is growing consistently, now with more than 100 customers, most based in Europe but with good uptake in the U.S.
Those customers praise the technology as offering good value when considering cost verses performance.
The combination of virtual schema development for external data sources and script language containers, along with existing parallel distribution, enables customers or partners to develop, deploy and execute their analytics algorithms on Exasol in any language.
Cautions: Lack of market visibility. This is likely to remain the case throughout 2016 as the company has opted to expand outside Europe mainly via partners.
Exasol scaled back its U.S. operations in 2015, despite recent successes there. The company did retain U.S.-based expertise for sales and customer support and appears positioned to re-enter North America in 2016.
Niche Player: Hitachi
Product: Hitachi Advanced Data Binder (HADB), offered in three configurations: desktop, "entry" model and "standard" model.
Those offerings are priced and delivered on the basis of expected capacity, number of processor cores and amount of memory.
Hitachi
Strengths: Tokyo-based Hitachi's road map focuses on addressing the demands of the Japanese market with its high-speed, traditional solution for structured data analytics that focuses on industry use cases.
Hitachi customers consider massive volumes of trade data, sensor data and even geological data to be structured data for analysis with HADB.
Cautions: Recently, Hitachi has been pursuing engagements in North America. But the data warehousing solution being sold in the Japanese market, while mature and efficient, is quite basic.
Hitachi barely qualified for inclusion in the Magic Quadrant because it saw only limited growth in 2015, Gartner noted, resulting in only a small number of production references.
Visionary: Hortonworks
Products: Hortonworks Data Platform (HDP) on Linux and Windows. A free, laptop-capable sandbox version of HDP is also available.
Hortonworks DataFlow (HDF) on Linux on an on-premises basis and through various cloud providers.
Microsoft Azure HDInsight for hybrid deployments.
Hortonworks
Strengths: Hortonworks, Santa Clara, Calif., became the first Hadoop distribution vendor to go public. That aggressive move back in December of 2014 was coupled with "a dedicated posture designed to prove the viability and relevance of Hadoop to enterprises."
Since then, Hortonworks has shown a significant increase in new customers.
Hortonworks has gained market traction through partners, including traditional DBMS vendors, with whom it avoids direct competition.
Cautions: Vendors like Teradata and Microsoft are also partnering with Hadoop distribution vendors, which poses a challenge for Hortonworks to maintain its differentiation.
Hortonworks' financial reports show that while the business is progressing as was planned when the company went public, potential challenges with market adoption lie in wait, given the enterprise-ready demands of a well-established data management for analytics market.
Challenger: Hewlett Packard Enterprise
Products: HPE Vertica, based on the core Vertica DBMS, a column store analytic DBMS. Vertica is available as a cloud solution, as a software-only option and as an appliance.
HPE Vertica for SQL on Hadoop for integration with Hadoop.
Challenger: Hewlett Packard Enterprise
Strengths: Customers rate HPE Vertica well in terms of value for their money -- a differentiator from other major vendors in the market.
Customers use HPE Vertica for a variety of use cases and types of data, which demonstrates adoption by leading-edge customers. "Additional investment in polyglot capabilities will fuel this trend," Gartner noted.
Cautions: Gartner hasn't seen a rise in the number of users of its client inquiry service who ask about HPE Vertica, indicating a market visibility challenge.
The formation of Palo Alto, Calif.-based HPE out of Hewlett-Packard could help address that issue.
Customers also indicate challenges with the overall administration and management of HPE's DBMS, although they point out it's gradually improving.
Leader: IBM
Product: Stand-alone DBMS solutions, data warehouse appliances, a z/OS solution, and a Hadoop distribution with BigInsights.
Appliances: IBM PureData System for Analytics, the IBM PureData System for Operational Analytics, the IBM DB2 Analytics Accelerator (IDAA) and the IBM Smart Analytics System.
IBM DB2 with Blu Acceleration, an in-memory technology for high-performance analytics.
DB2 as a data warehouse managed services and DashDB, a cloud data warehouse service.
IBM
Strengths: IBM, Armonk, N.Y., has rolled out dashDB and DataWorks as cloud offerings, enabling customers to rapidly deploy analytic models and data in an elastic environment.
And IBM's commitment to the Apache Spark open-source project will bring value to IBM's products by enabling streaming, machine learning and advanced analytics.
Cautions: While IBM reports significant adoption of dashDB, Gartner has received few client inquiries about the product. "Inquiries ought to be more numerous," Gartner noted.
While fluctuations in IBM's market share, growth and net revenue could be interpreted in many ways, "we think it is currently the result of retrenchment as IBM repositions its offerings for the modern cloud and data management solution markets."
Customers rated IBM in the lower third of surveyed vendors for overall value for money and identified pricing as an issue.
Challenger: Infobright
Products: A column-vectored, highly compressed DBMS under a MySQL- or PostgreSQL-based API layer.
The commercial Infobright Enterprise Edition (IEE), which allows a trial download.
Challenger: Infobright
Strengths: Speed of processing is a differentiator. Customers commended its compression, load rates and lack of a need for indexing.
Internet of Things (IoT) data presents a clear opportunity for Toronto-based Infobright, which is planning various technological innovations in that area.
Cautions: Some customers say some MySQL data types are not supported by Infobright's software, possibly caused by use of different versions. Customers mentioned the absence of certain features and a cumbersome upgrade process.
Infobright will continue to earn revenue among its traditional base as an OEM within networking, telecommunications and advertising technology sectors, "but we expect its results to be mixed as new analytics demands have emerged over the past four years and the market continues to change," Gartner notes.
Niche Player: Kognitio
Products: The Kognitio Analytical Platform, offered both as a software data warehouse DBMS engine and as an appliance.
Kognitio Analytical Services is a public or private cloud solution that's also available through Amazon Web Services.
Kognitio
Strengths: Kognitio, Bracknell, England, continues to focus strongly on technology, bringing to market capabilities tailored to the emerging demands of a few leading-edge customers, such as those requiring an analytical engine on Hadoop distributions.
"With plans for coexistence on Hadoop nodes and integration with Apache Hadoop YARN and Kerberos, as well as JSON parsing, Kognitio is likely to enhance its appeal as the universal processing engine for distributed analytics processing," according to Gartner.
Cautions: Building market presence and sales remains a challenge for Kognitio. It's hard to find people skilled in using its software and the community is small, which causes clients to suffer.
Kognitio's small installed base and limited vendor community make it challenging for customers to build a support network and identify best practices.
Visionary: MapR Technologies
Product: A Hadoop distribution with performance and storage optimizations, high-availability improvements, and administrative and management tools.
Visionary: MapR Technologies
Strengths: Clients praise MapR, based in San Jose, Calif., for its enterprise-readiness, high availability and cluster management. And MapR has only enhanced those capabilities with the addition of authorization and auditing features.
The technology supports streaming, operational and analytical use cases, all from the same platform, with multimodel support and SQL capabilities across all models.
MapR has been expanding across the world and has entered partnerships with major players, such as AWS, Google, HPE, IBM, Microsoft, SAP, SAS and Teradata.
Cautions: Despite MapR's progress, it still suffers from a lack of market visibility, as indicated by Gartner's receipt of fewer inquiries about MapR than other Hadoop distribution vendors.
Actual users appear to be advanced and highly skilled adopters who create analyses that are deployed as complete data products for use in production.
Challenger: MarkLogic
Product: An enterprise NoSQL database that uses XML, JSON, text, Resource Description Framework (RDF) triples and binary storage, and provides a strong metadata-driven semantic entity management layer.
The product includes indexes, tiered storage, Hadoop Distributed File System (HDFS) support, Amazon S3 support, mobile replication, full-text search, geospatial capabilities and SQL/ODBC support.
MarkLogic
Strengths: San Carlos, Calif.-based MarkLogic's growth has increased dramatically in the past three years, both in revenue and customers, helping the company advance on the Magic Quadrant's Ability-to-Execute axis.
Customers use the product on various forms of semi-structured data assets. Recent additions to optimization approaches that introduced statistics on use cases and how they relate to the data under management have improved administrative and design capabilities.
Cautions: MarkLogic is a small vendor with some distinctive capabilities driving demand, but it's competing in a large market against bigger vendors starting to deploy and improve similar solutions.
Customers complained of a lack of qualified expertise in the market, which poses a risk to growth. Some were also frustrated by functionality gaps and a lack of mature management/administrative tools.
Visionary: MemSQL
Product: An in-memory DBMS for transactional use cases, combined with a disk-based column store for analytics.
MemSQL
Strengths: "MemSQL's strategy focuses on supporting transactional and analytical use cases with low-latency requirements. Integration with Apache Spark enables stream ingestion, transaction processing and analytics," Gartner noted.
The San Francisco-based company entered the DBMS market in 2013 and is in the process of expanding into the data warehouse and DMSA market by addressing operational analytics use cases involving data from transactional application and other sources.
Cautions: Some customers said MemSQL's pricing was an issue and ranked it in the bottom third of the surveyed vendors for overall value for money. But MemSQL does offer a free community edition, and it doesn't charge for disk storage in its column store.
Leader: Microsoft
Products: For on-premises deployments: SQL Server, a reference architecture, and the Microsoft Analytics Platform System that combines SQL Server Parallel Data Warehouse and HDInsight.
For cloud deployments: Azure SQL Data Warehouse, still in preview, and Azure HDInsight for Hadoop.
Microsoft
Strengths: Microsoft's upcoming cloud-based solutions will include an analytics data environment. Although Azure SQL Data Warehouse is still in preview, it's already attracting strong customer interest.
Broad choices for deployment and the completeness of Redmond, Wash.-based Microsoft's products will challenge traditional vendors that focus on cloud and user-driven, self-service capabilities.
Customers commend Microsoft's security, scale and familiarity.
Cautions: Customers have identified occasional back-end and infrastructure issues.
Microsoft's market positioning for data management solutions for analytics in the cloud is unclear, and the software giant needs to clarify how it will simultaneously support the self-service audience and enterprise-class customers, Gartner says.
Niche Player: MongoDB
Product: An open-source document DBMS that provides a data model similar to JSON.
Offered as a cloud service or as on-premises software, MongoDB supports automatic sharding, failover, secondary indexes (including arrays), geospatial data and text search, as well as management tools.
MongoDB
Strengths: MongoDB, New York and Palo Alto, Calif., embraced by application developers, is known for processing operational data. The software is used frequently in an application-embedded manner, with analytic models deployed into applications using data integrated from additional sources.
Customers commended MongoDB's strength in operational analytics and its management interface, ease of tuning and easily surmounted learning curves.
Cautions: Although MongoDB has successful customer deployments for operational analytical needs, customers don't seem to identify the product as an enterprise analytics platform.
Some say they consider data management within MongoDB's DBMS to be a chore.
"MongoDB is embraced by application developers and architects, but it is difficult to find a data management expert willing to learn MongoDB's platform, primarily due to the lack of maturity of its data management functionality," Gartner noted.
Leader: Oracle
Products: Oracle Database 12c, the Oracle Exadata Database Machine, the Oracle Big Data Appliance, the Oracle Database Exadata Cloud Service (including 19 Tier-4 data centers worldwide), the Oracle Big Data Management System, Oracle Big Data SQL and Oracle Big Data Connectors.
Oracle
Strengths: Oracle customers say the combination of hardware and software in a single solution eases deployment and management. They're satisfied by the performance and stability of Oracle's engineered systems.
In 2015, Redwood City, Calif.-based Oracle reported a surge in adoption of the Oracle Big Data Appliance.
Broad analytic capabilities include the use of what Oracle describes as "any Hadoop" in combination with any Oracle Database 12c.
Cautions: Some Oracle customers and Gartner clients indicated concerns about the software's initial cost, maintenance cost and, therefore, overall value. And more customers were concerned about ease-of-use than was the case for other providers evaluated.
"Oracle does, however, serve a broad base of customers with a highly diverse range of skills," Gartner notes.
Gartner's clients also have consistently reported frustrations with Oracle's contracts, negotiations and ongoing costs.
Visionary: Pivotal
Products: Pivotal Greenplum and Pivotal HDB.
Pivotal also offers services via Pivotal Labs.
Big Data Suite combines and delivers these products.
Pivotal
Strengths: Pivotal, Palo Alto, Calif., challenges the market "with the idea that distributed processing can take any form in any data management system," Gartner said.
The company's pursuit of balanced workload management across different data stores, and even the optimization of analytics processes across differing processing languages, "may well be the future of data management for analytics."
Pivotal's customers report a broad range of benefits, from speed to distributed processing capacity to scalability and high availability.
Cautions: While open-source software-based data warehouse infrastructure may come to dominate the market after 2020, Pivotal's open-source strategy could be seen as premature in 2016.
And there's the chance that IoT providers will absorb significant functionality from open-source providers into their own platforms.
Customers also noted some important issues with Pivotal's software: high concurrency of access and query failure when a segment is down.
Leader: SAP
Products: SAP IQ, the first column-store DBMS, is available as a stand-alone DBMS.
SAP Hana is an in-memory column store that supports operational and analytical use cases.
Hana is also offered as an appliance, a cloud solution in SAP Hana Cloud Platform, and a reference architecture in SAP Hana tailored data center integration [TDI].
SAP also delivers SAP Business Warehouse (BW) on Hana.
SAP
Strengths: SAP, Walldorf, Germany, is succeeding with data warehousing use cases, with adoption of SAP Business Warehouse (BW) on Hana growing across its customer base.
SAP is also improving on the flexibility of its cloud deployment options and high-availability/disaster recovery capabilities.
Cautions: Despite all of SAP's positioning efforts, SAP Hana is still mainly being adopted by existing SAP customers. "This presents SAP with a challenge to expand its penetration of the market for analytics data management," Gartner noted.
And a lack of focus on SAP IQ reduces that product's potential for growth outside the company's installed base.
Customers identified challenges with SAP Hana that included functionality gaps, stability issues and a lack of available skills in the market.
Leader: Teradata
Products: A DBMS solution, data warehouse appliances and a cloud data warehouse solution.
Both traditional solutions and Logical Data Warehouse (LDW) solutions as part of its Unified Data Architecture (UDA).
A combination of tuned hardware and analytics-specific database software, which includes the Teradata Database on various form factors of appliance, Aster Analytics and Hadoop via all three major distributions, as well as analytic consulting services.
Teradata
Strengths: Teradata's products have evolved to meet demands of a changing market through an approach that offers customers flexibility and creates opportunities to adopt the products separately. Customers praised the software for its performance, scalability, workload management and rich features.
Cautions: The traditional appliance business is facing challenges.
"After 35 years of dominance with a revolutionary appliance (one emulated by almost every other major vendor in the past 10 years), Teradata is shifting to software components and cloud computing at the same pace as its clients, but later than some of its competitors," Gartner noted.
Teradata, Dayton, Ohio, is generally perceived as a stack vendor at a time when many organizations are looking to expand their technology portfolio piece by piece.
Visionary: Transwarp
Product: Transwarp Data Hub (TDH), a full suite of Hadoop distribution components, supplemented by an SQL engine, machine learning, NoSQL search engine and stream processing.
Transwarp
Strengths: The young vendor has gained traction in the Chinese market, winning 200 clients in less than 18 months. Transwarp, Shanghai, has a unique set of capabilities, and customers indicated they were very satisfied with the product, as well as with the support and training offered.
Cautions: Transwarp still operates only in China. And the company has yet to offer a cloud solution, although it has indicated that's on the road map. Customers also pointed to some missing functionality, particularly with regard to administration and management.
