Securely integrate Azure Synapse Analytics with Vertica Analytics Platform
About Azure Synapse Analytics
Azure Synapse Analytics is the next incarnation of Azure SQL Data Warehouse from Microsoft. Like SQL Data Warehouse, Azure Synapse Analytics is a cloud-based, relational data warehouse system with MPP (massively parallel processing), virtually unlimited scaling capacity, and the power to process and store petabytes of data. The difference is that Azure Synapse Analytics has added business intelligence, machine learning, and other advanced features to its data warehousing profile. Microsoft has also boosted the platform’s capacity to ingest, transform, manage, and process larger volumes of relational and non-relational data faster and more efficiently.
About Vertica Analytics Platform
Vertica Analytics Platform is a data warehouse management system optimized for large-scale, rapidly-growing datasets. By using a column-oriented architecture (instead of row-oriented), Vertica can offer high-speed query performance for your business intelligence, machine learning, and other query-intensive systems. Vertica is compatible with a variety of cloud data warehouse servers such as Google Cloud Platform, Amazon Elastic Compute Cloud, Microsoft Azure, and on-premises. The platform also offers its “Eon Mode,” which achieves optimum performance by separating computational processes from storage processes. Eon Mode is available when hosting the platform on AWS or when using Pure Storage Flashblade on-premises. Vertica is an open-source product that is free to use up to certain data limitations.
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Azure Synapse Analytics's End Points
Azure Synapse Business Intelligence, Machine Learning, and Data Analytics
In addition to serving as a powerful, scalable, cloud-based data warehouse, Azure Synapse adds advanced business intelligence and machine learning data analytics to its list of services.
Azure Synapse Unified Analytics
Whether you need a non-relational data lake, relational data warehouse, or a combination of both, Azure Synapse integrates the two and lets you query the data in SQL while serving as a unified, end-to-end analytics solution. Within a single workspace, Azure Synapse allows you to achieve your data warehousing, data preparation, data management, AI, machine learning, and business intelligence goals. Access all of your data and create stunning dashboards with Power BI via a single interface.
Azure Synapse Cloud-Native HTAP Implementation
With Azure Synapse Link, cloud-native HTAP implementation allows you to integrate Azure Synapse with Azure databases to extract near real-time insights from operational databases. This allows Azure Synapse to extract machine learning and business intelligence analyses from live data without disrupting the transactional performance of operational systems.
Azure Synapse Programming Language Compatibility
Azure Synapse allows your team to work with their preferred language. Whether it's T-SQL, Scala, Spark SQL, Python, or .Net, Azure Synapse is compatible with your language of choice while using either provisioned or serverless processing resources.
Azure Synapse Serverless On-Demand or Provisioned Resources
Azure Synapse lets you query data with provisioned or serverless on-demand computational resources.
Azure Synapse Compatibility With Azure, Microsoft, and Open Data Initiative Services
Azure Synapse natively connects with a wide range of Azure and Microsoft services. The platform includes native connectors for Azure Machine Learning, Azure Data Lake, Azure Blob Storage, Azure Active Directory for authentication, and Microsoft Power BI for visualizing data. Azure Synapse also integrates its machine learning and business intelligence tools with Open Data Initiative tools and services. Led by Microsoft, Adobe, and SAP Software solutions, the Open Data Initiative seeks to boost the connectivity and interoperability of cloud-based SaaS services. Open Data Initiative compatible services include the Microsoft Office 365 suite, the Microsoft Dynamics 365 suite, and more.
Azure Synapse Workload Optimization
Microsoft Azure Synapse makes it easy to optimize your query performance through limitless concurrency, workload isolation, workload management.
Azure Synapse Advanced Security and Privacy
Azure Synapse offers cutting-edge security and privacy that includes dynamic, real-time data masking, always-on data encryption, automated threat detection, authentication through single-sign-on and Azure Active Directory. The platform also includes access control features like column-level security and native row-level security for additional security and privacy within your team.
Azure Synapse Compliance Certifications
In terms of compliance, Azure offers more certifications than any cloud provider to ensure that your data collection and data use practices comply with industry-specific, regional, state, and national compliance standards.
Vertica Analytics Platform's End Points
Vertica Massively Parallel Processing (MPP)
Through its MPP architecture, Vertica distributes requests across different nodes. This brings the benefit of virtually unlimited linear scalability.
Vertica Column-Oriented Storage
Veritica's column-oriented storage architecture provides faster query performance when managing access to sequential records. This advantage also has the adverse effect of slowing down normal transactional queries like updates, deletes, and single record retrieval.
Vertica Workload Management Automation
With its workload management features, Vertica allows you to automate server recovery, data replication, storage optimization, and query performance tuning.
Vertica Machine Learning Capabilities
Vertica includes a number of machine learning features in-database. These include 'categorization, fitting, and prediction,' which bypasses down-sampling and data movement for faster processing speed. There are also algorithms for logistic regression, linear regression, Naive Bayes classification, k-means clustering, vector machine regression/classification, random forest decision trees, and more.
Vertica In-Built Analytics Features
Through its SQL-based interface, Vertica provides developers with a number of in-built data analytics features such as event-based windowing/sessionization, time-series gap filling, event series joins, pattern matching, geospatial analysis, and statistical computation.
Vertica SQL-Based Interface
Vertica's SQL based interface makes the platform easy to use for the widest range of developers.
Vertica Shared-Nothing Architecture
Vertica's shared-nothing architecture is a strategy that lowers system contention among shared resources. This offers the benefit of slowly lowering system performance when there is a hardware failure.
Vertica High Compression Features
Vertica batches updates to the main store. It also saves columns of homogenous data types in the same place. This helps Vertica achieve high compression for greater processing speeds.
Vertica Kafka and Spark Integrations
Vertica features native integrations for a variety of large-volume data tools. For example, Vertica includes a native integration for Apache Spark, which is a general-purpose distributed data processing engine. It also includes an integration for Apache Kafka, which is a messaging system for large-volume stream processing, metrics collection/monitoring, website activity tracking, log aggregation, data ingestion, and real-time analytics.
Vertica Cloud Platform Compatibility
Vertica runs on a variety of cloud-based platforms including Google Cloud Platform, Microsoft Azure, Amazon Elastic Compute Cloud, and on-premises. It can also run natively using Hadoop Nodes.
Vertica Programming Interface Compatibility
Vertica is compatible with the most popular programming interfaces such as OLEDB, ADO.NET, ODBC, and JDBC.
Vertica Third-Party Tool Compatibility
A large number of data visualization, business intelligence, and ETL (extract, transform, load) tools offer integrations for Vertica Analytics Platform. For example, Xplenty's ETL-as-a-service tool offers a native integration to connect with Vertica.