The adoption of Kubernetes-enabled infrastructures and applications has revealed the challenge involved in enabling persistent, reliable data storage in an ephemeral compute…
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GigaOm Radar for Machine Learning Operations
Machine learning operations (MLOps) solutions streamline machine learning (ML) model development, deployment, and governance, enabling production ML at scale. They simplify each…
Read MoreGigaOm Radar for Cloud File Systems
File storage is a critical component of every hybrid cloud strategy, and enterprises often prefer it over block and object storage, in…
Read MoreKey Criteria for Evaluating Machine Learning Operations Solutions
In recent years, the market for machine learning operations (MLOps) has seen rapid growth as businesses seek support for becoming machine learning…
Read MoreGigaOm Sonar Report for Storage as a Service
Storage as a service (STaaS) is a subscription-based model for data storage that provides customers with a cloud-like experience in terms of…
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Cloud Analytics Platform Total Cost of Ownership
Organizations today need a broad set of enterprise data cloud services with key data functionality to modernize applications and utilize machine learning.…
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Cloud Parallel File Systems
The latest organizational initiatives involving artificial intelligence (AI), machine learning (ML), high performance computing (HPC), and containerized application spaces necessitate a robust…
Read MoreKey Criteria for Evaluating Disaster Recovery and Business Continuity as a Service Solutions
Disaster recovery (DR) provides rapid restoration of one or more applications or systems when the data center where they reside is, or…
Read MoreGigaOm Radar for Network Validation
With business-critical services on the line, managing the network holistically is essential for ensuring operational consistency. Many enterprises address network governance with…
Read MoreGigaOm Radar for Machine Learning Operations
Machine learning operations (MLOps) solutions streamline machine learning (ML) model development, deployment, and governance, enabling production ML at scale. They simplify each…
Read MoreKey Criteria for Evaluating Machine Learning Operations Solutions
In recent years, the market for machine learning operations (MLOps) has seen rapid growth as businesses seek support for becoming machine learning…
Read MoreGigaOm Radar for Enterprise Business Intelligence
Business intelligence (BI) is today’s key enabler for analyzing data, deriving business insights from it, and sharing and publicizing those insights within…
Read MoreGigaOm Radar for Self-Service Business Intelligence
In recent years, self-service business intelligence (SSBI) has become an increasingly important tool for organizations of all sizes. Unlike enterprise BI (EBI),…
Read MoreKey Criteria for Evaluating Business Intelligence Solutions
Business Intelligence (BI) as a paradigm and product category has been around for decades. Arguably, though, it is enjoying its greatest popularity,…
Read MoreGigaOm Radar for Data Virtualization: Enterprise Vendors
The biggest obstacle that organizations face in using data to achieve mission-critical goals is the sheer variation in datasets that they encounter…
Read MoreGigaOm Radar for Data Virtualization: Pure-Play Vendors
The most challenging aspect of leveraging data for contemporary organizations isn’t the enormous quantity of data or the real-time speeds at which…
Read MoreGigaOm Radar for Data Quality Platforms: Detection of Data Quality Issues
The success of any data-related project depends on the quality of data. Enterprise customers manage massive amounts of data, and it’s imperative…
Read MoreGigaOm Radar for Data Quality Platforms: Data Quality Remediation
Data quality reflects the completeness, accuracy, reliability, and related attributes of data. There are numerous platforms for managing data quality designed to…
Read MoreKey Criteria for Evaluating Data Virtualization Solutions
The diversity of the data ecosystem within modern enterprises is one of the most difficult aspects of managing data today. Companies struggle…
Read MoreKey Criteria for Evaluating Data Quality Platforms
Data quality reflects the completeness, accuracy, consistency, usability, reliability, relevance, traceability, precision, statistical normality, verifiability, and error-free status of data. Poor data…
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Relational Databases in the Cloud: Masters of Federation
Relational database management systems (RDBMSes) have been around for a long time, and they are very much still with us. The on-premises…
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