Forrester Wave™: Multimodel Data Platforms, Q3 2021

 Multimodel data platforms represent the intersection of multiple data models such as document, graph, and relational in a single data platform, offering speed, scale, performance, integration, and security over the polyglot persistence model. Combining multimodel data types and models on large-scale memory helps deliver real-time, consistent, and trusted data to support new business requirements. Most organizations leverage multimodel data platforms to support microservices-based applications and a common data platform for customer 360, fraud detection, internet-of-things (IoT) analytics, and highly interactive edge applications.

As a result of these trends, multimodel data platforms customers should look for providers that:

• A platform that delivers built-in speed, scale, and security to meet your requirements.
• A platform that can support multimodel apps and insights quickly through automation.
• A roadmap that is as bold as your multimodel ambitions.

SAP (HANA, HANA Cloud), Oracle, MongoDB (Enterprise & Atlas), Marklogic, InterSystems, Microsoft (Azure Cosmos DB), Couchbase are the leaders in "Forrester Wave™: Multimodel Data Platforms, Q3 2021"

The Forrester Wave™: Dynamic Data Masking Solutions, Q3 2021

 Tech investment and customer needs for dynamic data masking are increasingly driven by privacy compliance requirements like GDPR and CPRA, in addition to requirements like HIPAA, PCI, and more.

Today there is a range of approaches to architecture and deployment options for dynamic data masking solutions; there is no right or wrong approach, only what is best suited for your environment and needs. Some dynamic data masking solutions are embedded in the database, while others integrate at the middle and application tier. Also, some solutions are available on-premises, while others leverage native cloud capabilities.

Check out the 'The Forrester Wave™: Dynamic Data Masking Solutions, Q3 2021'

The Forrester Wave™: Streaming Analytics, Q2 2021

 treaming analytics allows enterprises to understand what is happening now, in real time, by analyzing streaming data from multiple real-time data sources. Enterprise customers have great options for choosing a streaming analytics platform from tried-and-true vendors, public cloud service providers, open source, and startups. The common theme in all of these vendors is a focus on development tools, scalability, and adding ever-richer analytics capabilities. 

Google (Google Cloud Dataflow), Microsoft (Azure Stream Analytics), SAS (SAS Event Stream Processing), Oracle (GoldenGate Stream Analytics (GGSA))and Tibco Software (TIBCO Streams) are the leaders in "The Forrester Wave™: Streaming Analytics, Q2 2021"

Magic Quadrant for Multichannel Marketing Hubs 2021

 Digital marketing leaders use multichannel marketing hubs to deliver contextually relevant experiences on complex customer journeys. Unified customer profiles backed by predictive insights help orchestrate personalized, multichannel engagement. Use this research to identify suitable MMH solutions.

Gartner defines the multichannel marketing hub (MMH) as a technology that orchestrates a company’s communications and offers to customer segments across multiple channels. These include websites, mobile, social, direct mail, call centers, paid media and email. MMH capabilities also may extend to integrating marketing offers/leads with sales for execution in both B2B and B2C environments.

Salesforce, Adobe, Oracle, SAS, Acoustic & SAP are the leaders in "Magic Quadrant for Multichannel Marketing Hubs 2021"

The Forrester Wave™: Cloud Data Warehouse, Q1 2021

 Today, cloud data warehouse (CDW) solutions are changing the way we deliver modern analytics. They can provision any size data warehouse in minutes, auto-tune queries, scale resources such as compute and storage based on demand, and automatically upgrade to the latest version. To address the growing need for more integrated, real-time, and self-service analytics, CDW vendors continue to focus on native integration with data lakes and object stores; self-service to simplify access and administration for larger and more complex warehouses; and advanced capabilities on parallel processing, compression, partitioning, indexing, query optimization, and dynamic resource provisioning. The most common CDW use cases include customer analytics, AI/machine learning (ML)-based analytics, vertical-specific analytics, and real-time analytics.

Google (BigQuery), Microsoft (Azure Synapse Analytics ), Amazon Web Services (Redshift), Teradata (Teradata Vantage in the Cloud ), Oracle (Oracle Autonomous Data Warehouse) & Snowflake (Snowflake Data Cloud ) are the leaders in “The Forrester Wave™: Cloud Data Warehouse, Q1 2021”.

Magic Quadrant for Master Data Management Solutions 2021

 

By 2023, organizations with shared ontology, semantics, governance and stewardship processes to enable interenterprise data sharing will outperform those that don’t.

 Gartner defines master data management (MDM) as a technology-enabled business discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, governance, semantic consistency and accountability of an enterprise’s official shared master data assets.

 Informatica , TIBCO, Riversand and Semarchy are the leaders in “Magic Quadrant for Master Data Management Solutions 2021”.

Gartner Magic Quadrant for Cloud Database Management Systems 2020

 

By 2022, 75% of all databases will be deployed or migrated to a cloud platform, with only 5% ever considered for repatriation to on-premises.

 Gartner defines the cloud database management system (DBMS) market as being that for products from vendors that supply fully provider-managed public or private cloud software systems that manage data in cloud storage. Data is stored in a cloud storage tier (such as a cloud object store, a distributed data store or other proprietary cloud storage infrastructure), and may use multiple data models — relational, nonrelational (document, key-value, wide-column, graph), geospatial, time series and others.

 AWS, Microsoft, Google, Oracle, IBM, SAP, Teradata & Alibaba Cloud are the leaders in “Gartner Magic Quadrant for Cloud Database Management Systems 2020".