Netapp, Inc.

Amazon Technologies, Inc.

Microsoft Technology Licensing, LLC

Datrium, Inc.

Vmware, Inc.

Microsoft Corporation

Gokul Soundararajan

Lakshmi Narayanan Bairavasundaram

Kaladhar Voruganti

Vipul Mathur

Sanuj Basu

Ippokratis Pandis

Deepak Kenchammana-hosekote

Ricardo Labiaga

Aditya Subrahmanyan

Gopal Paliwal

Yannis Papakonstantinou

Vuk Ercegovac

Sriram Krishnamurthy

Vijayan Prabhakaran

Krishna Chaitanya Gudipati

George Constantin Caragea

Balakrishnan Narayanaswamy

Rukma Ameet Talwadker

Mark Walter Storer

Punit Rajgaria

Priya Sehgal

Darren Sawyer

Madalin Mihailescu

Nikolaos Koulouris

Craig Chadwell

Jiayuan Chen

Vadim Skipin

Swaminathan Sivasubramanian

Steven Robert Kleiman

Garth Richard Goodson

Kiran Nenmeli Srinivasan

Shankar Pasupathy

Gaurav Saxena

Naresh Chainani

Sriram Subramanian

Rajesh Sudhakar Sheth

Shailaja Kamila

Grant A M McAlister

James Hartwell Holl, Ii

Murali Brahmadesam

Swetha Krishnan

Hemanth Satyanarayana

Ravi Krishna

Matthew Perry Abrams

Frederick Ryan Johnson

Fabian Oliver Nagel

Mahesh Balakrishnan

Induja Sreekanthan

Subramaniam Mohan

Aleksandr Mirgorodskiy

Naga Raju Bhanoori

Sanjay Wangoo

Todd Jeffrey Green

Jeffrey Zabarsky

Sethuraman Subbiah

Venu Gopal Nayar

Yiying Zhang

Hebatalla Mohamed Mohamed Aly Eldakiky

Rajesh Parangi Sharabhalingappa

Tanya Shastri

Lakshmi Narayanan Bairavasunda

Ankil Shah

Yao Xiao

Siyi Zhang

Yehan Zhang

Vaishali Ravindra Narkhede

Johannes Wust

Efficient superblock data structures are implemented for a data set. A superblock data structure, a log to commit changes to a superblock data structure, and an auxiliary data structure may be updated when an update to a data set is performed. The update may update respective location headers in the auxiliary data structure and the superblock data structure.

Efficient superblock data structures for database systems

It is detected that a metric associated with a first workload has breached a first threshold. It is determined that the first workload and a second workload access the same storage resources, wherein the storage resources are associated with a storage server. It is determined that the metric is impacted by the first workload and the second workload accessing the same storage resources. A candidate solution is identifier. An estimated impact of a residual workload is determined based, at least in part, on the candidate solution. A level of caching of at least one of the first workload or the second workload is adjusted based, at least in part, on the estimated impact of the residual workload.

Dynamic instantiation and management of virtual caching appliances

Methods for replicating transactional tables of a transactional database to an analytical database and maintaining updates to those transactional table representations are disclosed. Snapshots of the transactional tables are provided to the analytical database via a transport mechanism, such as a data storage service or a data streaming service, and stored at the analytical database. Then, checkpoints comprising portions of a change-data-capture log that has recorded transactional changes to the transactional tables of the transactional database are provided to the analytical database via the same or different transport mechanism and used to commit those transactional changes to the snapshot representations. The snapshot representations may be used to respond to incoming analytical queries in order to provide real-time querying results.

Hybrid transactional and analytical processing architecture for optimization of real-time analytical querying

Methods for negotiating parameters for maintaining, at an analytical database, a replica of a transactional table, stored at a transactional database, are disclosed. By establishing parameters of said maintenance prior to commencing, the transactional database and the analytical database may remain only loosely coupled after completing the negotiation. The parameters of the negotiation may be stored in a location that is accessible to both the transactional database and the analytical database, such that the results of the negotiation may be accessed during the process of maintaining the replica. The negotiation may include a procedure to provide portions of a change-data-capture log, associated to the transactional table, to the analytical database via a transport mechanism such that the replica may be updated, in addition to a list of agreed upon data definition language commands that may be used in the portions of the change-data-capture log.

Handshake protocol for efficient exchange of transactional information for a hybrid transactional and analytical processing architecture

Methods for implementing insert, update, and delete events of a change-data-capture log in transactional order to a representation of a transactional table are disclosed. Insert events may be applied and committed to the representation, while delete events may be buffered and committed to a shadow table. Such buffering may allow the delete events to be applied and committed as a batch to the given representation as a later background operation, allowing for an optimized application of the change-data-capture log to the representation. Once the delete events are committed to the representation, they are removed from the shadow table. Update events may be similarly treated in which the insert event component of the update event is applied and committed to the representation while the delete event component is committed to the shadow table, before being later committed to the representation and removed from the shadow table.

Optimization of application of transactional information for a hybrid transactional and analytical processing architecture

Online restore may be performed between databases with different topologies while applying a custom data distribution. A request to restore a database into a different topology of nodes may be received. A plan to move different portions of the database from a current topology to the new topology made using a general distribution scheme. The plan may be performed to move the different portions of the database into the new topology and the database made available for access using the new topology. A background process may be applied to modify the distribution of the database at the new topology to match a custom distribution scheme that was implemented at the current topology.

Online restore to different topologies with custom data distribution

A database system may use a machine learning model creation system to create a machine learning model from data stored in the database system responsive to a request from a client. The database system may obtain an executable version of the machine learning model, based on an uncompiled hardware agnostic version of the machine learning model, according to the hardware configuration of one or more computing resources selected by the database system to perform requests to the database system that invoke the machine learning model to generate predictions.

Dynamic compilation of machine learning models based on hardware configurations

A database system may include a machine learning model which may be used to perform various data analytics for data stored in the database system. In response to a request to invoke the machine learning model to generate a prediction from data stored in the database system, the database system may perform one or more optimization operations, as part of a query plan, to prepare the data to make it suitable for use by the machine learning model.

Integrating query optimization with machine learning model prediction

Techniques for resizing a distributed database are described. A request to resize a distributed database is received. The distributed database stores data organized into one or more rows of one or more tables. Each node of the first plurality of nodes is assigned a portion of the data. A portion of the data assigned to a first node in the first plurality of nodes is selected to be assigned to a second node in a second plurality of nodes. The number of nodes in the first and second plurality of nodes is different, and the first and second plurality of nodes include at least one common node. Metadata of the selected portion of the data is transferred from the first node to the second node. The metadata that includes a location of the selected portion of the data within a provider network.

In place resize of a distributed database

Technology is described for a profile-based lifecycle management for data storage servers. The technology can receive a profile, monitor events emitted by devices of the data storage system, determine based on the monitored events that a device of the storage system matches the indicated condition, and perform the action corresponding to the indicated condition, wherein the action includes managing data stored by the data storage system. The received profile can indicate a condition and an action corresponding to the condition.

Fabric attached storage

Technology is disclosed for managing network storage services by service level objectives (SLOs). The method receives multiple service level capability (SLC) templates; creates at least one storage service level (SSL) instance using at least one of the SLC templates; provisions a storage object located in a network storage infrastructure based on the SSL instance; and services storage requests using the storage object.

Network storage management at scale using service level objectives

Dynamic installation and management of virtual caching appliances

Techniques for monitoring and sending network connectivity information for connection pathways to host machines is provided. A storage node comprises a plurality of attached network interfaces and is operatively coupled to storage devices that are accessible to the host machines through network interfaces attached to the storage node. Each of the network interfaces send messages to the host machines. The storage node, receives host messages from at least one host machine. The storage node determines connectivity information about connectivity between network interfaces and host machines. The storage node receives a request for data that is stored on the one or more storage devices, from a host machine, at a target network interface, where the target node was chosen by the host machine based upon the connectivity information.

Data path monitoring in a distributed storage network

Technology is described for actively responding to data storage traffic. The technology can provide an application program interface; receive, via the application program interface, from an application, a command to query a data storage attribute associated with a virtual data storage component; query the associated virtual data storage component; and return to the application a value for the data storage attribute.

Actively responding to data storage traffic

Growing community of inventors

Sunnyvale, CA, United States of America

Gokul Soundararajan