Gartner Magic Quadrant Cloud Data Warehouse 2021 – In the past, companies built their business intelligence systems from the ground up, often starting with a traditional database. But as the volume, path and types of data explode, companies are looking for more efficient solutions to strengthen their analytics strategies. The state of the art in this software genre is what Gartner calls a Data Management Solution for Analytics (DMSA), or “analytics hub.”
According to Gartner, a DMSA is “a complete software system that supports and manages data across one or more file management systems, usually a database or multiple databases.” Depending on the data model in use—such as relational, XML, JSON, key-value, geospatial, or graph—DMSA can take many different flavors, be it traditional SQL analytics, machine learning, or graph processing.
Gartner Magic Quadrant Cloud Data Warehouse 2021
Nineteen vendors made the cut for Gartner’s “Magic Quadrant for Data Management Solutions for Analytics,” released last week.
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This includes eight in the Leaders quadrant, one Visionary quadrant, and 10 in the Crowded Niche Players quadrant. Gartner analysts Adam Ronthal, Roxanne Edgellali and Rick Greenwald noted that DMSA’s team has two combined teams, with no vendor making it into the Challenge quadrant.
The best vendors can address all DMSA use cases and are constantly optimizing their solutions to meet changing requirements. That said, all the leaders have cloud strategies and all have a vision “to address the broader DMSA market beyond traditional data storage,” the authors write.
As DMSA providers become benchmarks based on these approaches, the era of cloud disruption and disconnected technologies is over, says Gartner. That means big vendors are “rediscovering” their strengths, says Gartner, pushing good products out of the mainstream.
Oracle tightly controls the DMSA environment with autonomous data storage provisioning. The closest vendors to Oracle are AWS and Microsoft Azure, which offer cloud-first solutions bought by the vendors with a “strong vision” and funding. SAP scores highly in the DMSA, but its general purpose (ie unrelated to SAP offerings) means it’s not yet ready to challenge the industry leaders.
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Snowflake Computing and Google are newcomers to the Magic Quadrant. Gartner likes Snowflake’s growth and speed in its efforts to boost Google’s enterprise sales.
Persistent leaders Teradata and IBM have “struggled to maintain their market position in recent years,” Gartner said. IBM’s move from NetEnt to DB2 technology has received mixed reactions from its user base, and its core products are less flexible and efficient than newer competitors, according to Gartner. Teradata, on the other hand, continues to lead in technical product capabilities, but will suffer in market awareness as it moves to the cloud.
The only vendor that made the cut in the visionary category was MarkLogic, which develops multimodal NoSQL databases. Gartner announced its cloud offering and pricing model, but questioned whether users would understand its value as an analytics hub.
Gartner grouped Hadoop DMSA vendors — Cloudera, MapR and Hortonworks (which merged with Cloudera) — into its own group in the Challenger quadrant. These vendors have strengths in supporting data lakes and context-agnostic use cases, Gartner says, but are struggling to meet the needs of traditional data warehouses and have not yet completed the transition to the cloud.
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The second group of challengers is made up of growing Chinese companies including Alibaba Cloud, GBC and Huawei. Although Gartner calls the products “generally capable,” the analyst firm noted that they are still mainly used in the Asia-Pacific region and face headwinds for use in North America and Europe.
Neo4j is another challenger with a strong history in one area: graph processing. Gartner likes that Neo4j is the leading provider in the chart and how easy it is for users to get started. But limited off-the-charts applicability reduced DMSA’s rating.
ARM-acquired Treasure Data received high marks for its customer data platform, scoring well for customer satisfaction and cross-industry reach. But customers wanted it because of the complexity and cost of the product.
Pivotal has gotten good marks with the GreenPlum database, which users find efficient, scalable and open. But the lack of maturity and sophistication of cloud offerings weighed on the bottom line.
Microsoft Power Bi I Gartner Magic Quadrant I Karabina I South Africa
MicroFocus is the new home of Vertica’s MPP offering, which has been praised by Gartner for its analytics and data capabilities. But declining market share and divided opinion, as well as a gradual move to the cloud, weighed on the rating.
Vendors: Alibaba, Amazon, ARM, Cloudera, GBase, google, Hauwei, IBM, Marklogick, Micro Focus, Neo4j, Oracle, pivotal, SAP, Snowflake, Teradata.
Tags: big data , data analytics , data management solution for analytics , data mining , data warehouse , DMSA , Gartner , graph processing , NoSQL , relational database , sql
Microsoft Recognized As A Leader In The 2022 Gartner® Magic Quadrant™ For Cloud Erp For Product Centric Enterprises
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All cookies that may not be particularly necessary for the operation of the website and are used to collect user personal data for analysis, advertisements and other embedded content are called non-essential cookies. It is mandatory to obtain user consent before running these cookies on your website. We are thrilled that Gartner has named Google a leader in the 2021 Gartner® Magic Quadrant™ Cloud Database Management Systems (DBMS) for the second year in a row.
The report reviewed Google’s integrated marketing and analytics use cases and we believe it has progressed through innovations such as data management consistency, high processing and input speed, security, elasticity, advanced analytics, and more.
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With the recent announcement of DataPlex, organizations can manage, control, and manage their data across data lakes, data warehouses, and point-of-sale with consistent control. Solutions like BigQuery ML provide a “built-in” approach to advanced analytics capabilities, and Analytics Hub provides the infrastructure customers need to securely and widely share data analytics solutions in ways never before possible. For example, in a seven-day period in April, more than 3,000 different organizations shared more than 200 petabytes of data using BigQuery.
Research shows that 90% of organizations have a multi-cloud strategy, which is why we’ve invested in a cloud data analytics solution with BigQuery Omni for Google Cloud, AWS and Azure. In addition, our advancements with Antos and distributed cloud over the past year increase our ability to support multi-cloud and hybrid cloud scenarios. To gain a competitive advantage by leveraging data, organizations need an information platform that can handle marketing and analytics workloads with high levels of reliability, availability, and security. Cloud Spanner, our global distributed relational database, has redefined scalability, global consistency and online transaction processing (OLTP) systems. Spanner handles more than a billion requests per second at peak speeds, and has been battle-tested against the most demanding apps, including Google services like Search, YouTube, Gmail, Maps, and Payments. And what’s unique about our core services, Spanner and BigQuery, is that they leverage common infrastructure like our highly durable distributed file system (Colossus), our massive cluster management system (Borg) and Jupiter, a high-performance network infrastructure. Features such as connections between Spanner and BigQuery.
We focus on integrating Google Trends, Maps, Search, Ads and have industry domain expertise in areas such as retail, financial services, healthcare and gaming. We continue to produce industry white papers like this one – How to develop global multiplayer games using Cloud Spanner – and are proud of the team’s work to create and share industry patterns and horizontal architectures built from industry leaders to act as solution accelerators. User usage issues.
We continue to look for innovations in our Data Cloud portfolio, particularly those we announced at Google Cloud NEXT’21. BigQuery Omni is now available for AWS and Azure, supporting cross-cloud analytics for customers. We recently added more business data management and administration capabilities with Dataplex, which is GA. We’ve made migration to Cloud SQL easy with our database migration service. Over 85% of all migrations are underway in less than an hour, and most users are migrating their databases from other clouds. By adding the PostgreSQL interface, we’re embracing transparency with Spanner, enabling companies to take advantage of Spanner’s unmatched global scale, 99.999% availability, and strong consistency capabilities and tools.
Analytic Databases (data Warehousing)
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