Microsoft Technology Licensing, LLC

Karthik Raman

Dharma Kiritkumar Shukla

Shireesh Kumar Thota

Madhan Gajendran

Momin Mahmoud Al-Ghosien

Pankaj Sharma

Atul Katiyar

Ankur Savailal Shah

Kenneth David Wolf

Ji Huang

Hari Sudan Sundar

Mikhail Mikhailovich Koltachev

Liang Li

Sujit Vattathil Kuruvilla

Edmund Samuel Victor Pinto

Nathan Christopher Talbert

Shreshth Singhal

Ovidiu Constantin Platon

Nicholas Alexander Allen

Akash Jeevan Sagar

Justin David Brown

Quetzalcoatl Bradley

Constantin Dulu

John MacIntyre

Mark Connolly Benvenuto

Bhalakumaaran Erode Ranganathan

Elisa Marie Flasko

Samer Boshra

Rajeev Sudhakar Bhopi

Nemanja Matkovic

Subramanyam Pattipaka

Krishnan Sundaram

Digvijaysinh Govindbhai Makwana

John Anthony Taylor

Aditya G Bhandarkar

Mayank Mehta

Arsalan Ahmad

Farookh P Mohammed

Nishant Gupta

Adrian Ilcu Predescu

Karan Vishwanath Popali

Brandon Chong

Aravind Ramachandran Krishna

Todd R Manion

Andrew James Edwards

Paul Nathan Bennett

Saad Syed

Raymond Edward Endres

Pavel Anatolievich Dournov

Stefan R Batres

Ori Amiga

Robert Brian Schmidt

Kevyn Breca Collins-Thompson

Willis Lang

David Leon Stucki

Corey M Sanders

Hemant Kumar

Jayanta Mondal

Edmund S V Pinto

Oliver Drew Leonard Towers

Siddhesh Dilip Vethe

Nitin Sharma

Vinod Sridharan

Maxim Khutornenko

Bob Schmidt

Padma Priya Aradhyula Bhavani

Kiran Kumar Kolli

Emily Lawton

Orestis Kostakis

Balachandar Perumalswamy

Vivek Ravindran

Ashwini Singh

Mohammad Derakhshani

Denis Rystsov

Junyan Guo

Swarnim Vyas

Artavazd Ginosian

Lalitha Manjapara Viswanathan

Venkata Sivaramakrishna Ramadugu

Edmund Sv Pinto

Stefen R Batres

A method of bridging a first database and a second database. The method includes maintaining a state machine representing a state of a virtual node in the first database, wherein the state of the virtual node conforms to a native protocol for native nodes of the first database, said native protocol of the first database differing from a foreign protocol of the second database. The method further includes receiving an incoming message for the virtual node from one of the native nodes according to the native protocol, and based on the incoming message, accessing the second database. The method further includes updating the state of the virtual node based on the incoming message according to the native protocol, and based on the state of the virtual node as updated, sending an outgoing message to one or more of the native nodes according to the native protocol.

Controller for bridging database architectures

A server set for a data set may designate a subset of 'master' servers that update the data set in order to reduce data version conflicts involving mutually exclusive updates of the data set. Multi-master configurations may fulfill the performance constraints, and the subset of masters may detect and resolve data version conflicts. However, if multiple masters perform conflict resolution for a particular data version conflict, the resolution may produce inefficiency and redundancy (if the masters reach the same outcome) or additional data version conflicts (if the masters reach different outcomes). Instead, among the masters, a merge master may be identified that applies conflict resolution techniques to data version conflicts and forwards the conflict resolution outcome to the other masters for application to the data set to resolve the data version conflict. The other masters may temporarily store updates in a tentative update set until data version conflicts are resolved.

Merging conflict resolution for multi-master distributed databases

Data services for workloads are often provided with a service level agreement specifying various performance guarantees (e.g., latency, availability, scalability, and consistency). Single-master architectures, in which updates to the data set are constrained to a single server, may limit the fulfillment of some performance guarantees. Presented herein are multi-master architectures, in which the server set is partitioned into at least two masters are permitted to update the data set and at least one non-master that is not permitted to update the data set. Non-masters that receive a request to update the data set forward the request to a master server for application to the data set. A master that receives the request applies it to the data set and propagates the update to other master and non-master servers. Conflicting updates may be resolved through a variety of conflict resolution techniques, optionally designating one master server as a conflict resolution server.

Multi-master architectures for distributed databases

Data services are often provided with various performance guarantees. Multi-master architectures, in which multiple master servers are permitted to update a portion of the data set, may facilitate some performance requirements, but may also lead to data version conflicts in which different masters have written different versions of one or more data items. Moreover, conflicts involving different data items may have to be resolved using different conflict resolution techniques. Therefore, various data items of the data set may be associated with a conflict resolution technique selected from a conflict resolution technique set, such as manual conflict resolution; a write order policy, such as last writer wins; a conflict resolution logic; and conflict resolution based on data types. A data version conflict may be resolved by identifying and invoking the selected conflict resolution technique that is associated with the data item, and applying the conflict resolution outcome to the data item.

Conflict resolution for multi-master distributed databases

Distributed transactions are performed over a collection of servers operating as replicas of a data set, where a successful transaction involves meeting a quorum count of replicas that locally commit the transaction. However, performance constraints of data sets and consuming applications may vary (e.g., sensitivity to latency, scalability, and/or consistency), and the performance characteristics of the server set may be partly determined by the transactional commitment and quorum selection. The distributed transaction may be applied by designating the replicas as a set of followers and a leader that initiates the transaction and receives acknowledgments of local commits by each follower. On condition of the acknowledgments meeting a quorum count for the data set according to the performance characteristics of the application, the leader locally commits the transaction and delivers a result. The transaction may also be applied over collections of replica sets using a second-level quorum to achieve nested consensus.

Resource-governed protocol and runtime for distributed databases with consistency models

An application on a device may interact with a document service that provides access to a document service. The interaction may occur in a variety of contexts, such as a device context (e.g., the document service and the application provided on the same device), a local context (e.g., via a LAN), and a remote context (e.g., over the Internet). It may be advantageous to adapt the interaction to the current context, while also providing a consistent application interface that alleviates the application from context-specific implementations, and also achieving this adaptation in a performant manner. These considerations may be achieved in a balanced manner by providing a set of runtimes, where each runtime mediates the application/document service interaction between the application and the document service in a contextually adapted manner. The device may automatically detect the context of the interaction and select a contextually suitable runtime to service the application.

Available, scalable, and tunable document-oriented storage services

Data sets such as databases are often distributed over a number of servers, where each server stores a subset of records and an index that enables the server to locate the records in response to queries. However, tight coupling of indexing and storage may limit load-balancing, fault recovery, and distribution. Instead, the set of servers may be partitioned into a set of storage servers that store the records and a set of index servers of the index over the records. In a set that is decoupled in this manner, load-balancing may involve provisioning and locating index servers independently of the provisioning and locating of the storage servers in view of the particular sensitivities and tolerances of various applications. Additionally, the index servers may also utilize a data layout that is selected and adapted independent of the data layout of the storage servers and/or the schema of the data stored thereby.

Schema-agnostic indexing of distributed databases

Data services are often provided with consistency guarantees of either strong consistency models, comprising uniform wall-clock consistency, or eventual consistency models, where temporary logical inconsistency is guaranteed to be resolved only after full data propagation. However, the performance characteristics of contemporary services often require an intermediate consistency model, where some aspects of the service have specific consistency expectations and other aspects of the service are flexible, such as bounded staleness (e.g., a maximum delay in reaching consistency); session consistency (e.g., individual sessions remain logically consistent, but ordering may vary across sessions); and prefix consistency (e.g., each view during a session is logically consistent, but ordering may vary between session views). Service guarantees may involve a selection within a range of consistency models that includes one or more intermediate consistency levels, and server configurations may be selected and applied to fulfill the intermediate consistency level selected in the service level agreement.

Intermediate consistency levels for database configuration

Databases are often provided according to various organizational models (e.g., document-oriented storage, key/value stores, and relational database), and are accessed through various access models (e.g., SQL, XPath, and schemaless queries). As data is shared across sources and applications, the dependency of a data service upon a particular organizational and/or access models may become confining. Instead, data services may store data in a base representation format, such as an atom-record-sequence model. New data received in a native item format may be converted into the base representation format for storage, and converted into a requested format to fulfill data requests. Queries may be translated from a native query format into a base query format that is applicable to the base representation format of the data set, e.g., via translation into an query intermediate language (such as JavaScript) and compilation into opcodes that are executed by a virtual machine within the database engine.

Unified data organization for multi-model distributed databases

A data service may be distributed over a set of servers in order to provide a database with properties such as low latency, high availability, and support for various consistency levels. Presented herein is a particular architecture that promotes rapid provisioning to promote scalability and failover; adaptive load-balancing to accommodate fluctuations in demand; and resiliency in the event of various types of failure, such as network partitions or regional outages. For a service comprising a resource set, a container is provided that hosts a set of replicas of a partition, and that is assigned an allocation of computing capabilities of one or more servers. The resource set of the service may be distributed over the replicas of the container. Scalability is achieved by adding replicas to the container, and load-balancing may be provided by splitting, merging, or otherwise refactoring the partition to accommodate anticipated and unanticipated fluctuations in service demand.

Containerization for elastic and scalable databases

Workloads are often performed by a server set according to a service level agreement, and are often provisioned and load-balanced by dedicating selected computational resources (e.g., servers and bandwidth) for application to the workload. However, resource-based provisioning may not accurately reflect the computational resource expenditure of the workload, leading to overprovisioning or underprovisioning of servers for the workload. Instead, the workload may be evaluated according to a service unit as a measurement of a volume of computational resources consumed by a workload unit, including performance dimensions specified in the service level agreement. The service level agreement may indicate a service unit rate for the workload. The workload may therefore be allocated to a subset of servers in portions according to a service unit rate, where the sum of the service unit rates for the portions allocated to the servers satisfies the service unit rate specified in the service level agreement.

Data service provisioning, metering, and load-balancing via service units

A server set may provide a document service to various clients in view of considerations such as availability, fault tolerance, flexibility, and performance. Presented herein are document service architectures that involve partitioning the document set into at least two document ranges, and assigning the respective document ranges to an agent that is deployed to at least one assigned server. A request to apply an operation to a selected document may be fulfilled by identifying the document range of the document; identifying a selected server of the server set that hosts the agent to which the range is assigned; and forwarding the request to the selected server. In some variations, servers may retain detailed information about neighboring servers (e.g., according to logical and/or physical proximity) and scant information about distant servers, thereby avoiding both the extensive information exchange of highly informed network architectures and the inefficiency of uninformed routing algorithms.

Elastically scalable document-oriented storage services

A server set may provide a document service to one or more clients, and may be configured to do so in view of various considerations such as availability, fault tolerance, flexibility, and performance. Presented herein are document service architectures that involve partitioning the document set into at least two document ranges, and configuring respective servers of the server set to host one or more agents to which are respectively assigned one or more document ranges. A request for an operation involving at least one document may be routed to a server hosting an agent managing the document ranges of the documents involved in the operation. Moreover, respective servers may retain detailed information about neighboring servers (e.g., according to a logical or physical proximity) and scant information about distant servers, thereby avoiding both the extensive information exchange of highly informed network architectures and the inefficiency of uninformed routing algorithms.

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Issaquah, WA, United States of America

Karthik Raman