Alec Grieser

dblp:234/7563 · DBLP profile ↗
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3ranked-venue papers
0as first author
2since 2021 · last 2021
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 3 · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
3 papers
Storage systems · 54% Cloud and datacenter computing · 29% Distributed systems · 18%
Databases, data mining, and information retrieval
1 paper
Database system architecture and tuning · 50% Indexing and storage engines · 50%

Topics — the 7 heaviest of 9, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Distributed systems › distributed database
distributed transactions
0.512021
FoundationDB: A Distributed Unbundled Transactional Key Value Store · SIGMOD Conference 2021
Storage systems
key-value storage
0.512021
FoundationDB: A Distributed Unbundled Transactional Key Value Store · SIGMOD Conference 2021
Storage systems
storage reliability
0.512021
FoundationDB: A Distributed Unbundled Transactional Key Value Store · SIGMOD Conference 2021
Storage systems › key-value storage
transactional key-value store
0.512021
FoundationDB: A Distributed Unbundled Transactional Key Value Store · SIGMOD Conference 2021
Indexing and storage engines
secondary index
0.412019
FoundationDB Record Layer: A Multi-Tenant Structured Datastore · SIGMOD Conference 2019
Cloud and datacenter computing
cloud infrastructure
0.112021
FoundationDB: A Distributed Unbundled Transactional Key Value Store · SIGMOD Conference 2021
Cloud and datacenter computing › multi-tenancy
tenant isolation
0.112021
QuiCK: A Queuing System in CloudKit · SIGMOD Conference 2021

Methods — techniques the papers use, named apart from their topics

schema management · 0.8indexing · 0.8two-level sharding · 0.5deterministic simulation · 0.5FoundationDB Record Layer · 0.5
YearPublicationVenuePosition
2021 QuiCK: A Queuing System in CloudKit
abstract
We present QuiCK, a queuing system built for managing asynchronous tasks in CloudKit, Apple's storage backend service. QuiCK stores queued messages along with user data in CloudKit, and supports CloudKit's tenancy model including isolation, fair resource allocation, observability, and tenant migration. QuiCK is built on the FoundationDB Record Layer, an open source transactional DBMS. It employs massive two-level sharding, with tens of billions of queues on the first level (separately storing the queued items for each user of every CloudKit app), and hundreds of queues on a second level (one per FoundationDB cluster used by CloudKit). Our evaluation demonstrates that QuiCK scales linearly with additional consumer resources, effectively avoids contention, provides fairness across CloudKit tenants, and executes deferred tasks with low latency.
Kfir Lev-Ari, Yizuo Tian, Alexander Shraer, Chris Douglas, Andrey Andreev, Kevin Beranek, Scott Dugas, Alec Grieser, Jeremy Hemmo
SIGMOD Conference9
2021 FoundationDB: A Distributed Unbundled Transactional Key Value Store
abstract
FoundationDB is an open source transactional key value store created more than ten years ago. It is one of the first systems to combine the flexibility and scalability of NoSQL architectures with the power of ACID transactions (a.k.a. NewSQL). FoundationDB adopts an unbundled architecture that decouples an in-memory transaction management system, a distributed storage system, and a built-in distributed configuration system. Each sub-system can be independently provisioned and configured to achieve the desired scalability, high-availability and fault tolerance properties. FoundationDB uniquely integrates a deterministic simulation framework, used to test every new feature of the system under a myriad of possible faults. This rigorous testing makes FoundationDB extremely stable and allows developers to introduce and release new features in a rapid cadence. FoundationDB offers a minimal and carefully chosen feature set, which has enabled a range of disparate systems (from semi-relational databases, document and object stores, to graph databases and more) to be built as layers on top. FoundationDB is the underpinning of cloud infrastructure at Apple, Snowflake and other companies, due to its consistency, robustness and availability for storing user data, system metadata and configuration, and other critical information.
Jingyu Zhou, Meng Xu 0023, Alexander Shraer, Bala Namasivayam, Evan Tschannen, Steve Atherton, Andrew J. Beamon, Rusty Sears, John Leach, Dave Rosenthal, Will Wilson, Ben Collins, David Scherer, Alec Grieser, Young Liu, Alvin Moore, Bhaskar Muppana, Xiaoge Su, Vishesh Yadav
SIGMOD Conference16
2019 FoundationDB Record Layer: A Multi-Tenant Structured Datastore
abstract
The FoundationDB Record Layer is an open source library that provides a record-oriented data store with semantics similar to a relational database implemented on top of FoundationDB, an ordered, transactional key-value store. The Record Layer provides a lightweight, highly extensible way to store structured data. It offers schema management and a rich set of query and indexing facilities, some of which are not usually found in traditional relational databases, such as nested record types, indexes on commit versions, and indexes that span multiple record types. The Record Layer is stateless and built for massive multi-tenancy, encapsulating and isolating all of a tenant's state, including indexes, into a separate logical database. We demonstrate how the Record Layer is used by CloudKit, Apple's cloud backend service, to provide powerful abstractions to applications serving hundreds of millions of users. CloudKit uses the Record Layer to host billions of independent databases, many with a common schema. Features provided by the Record Layer enable CloudKit to provide richer APIs and stronger semantics with reduced maintenance overhead and improved scalability.
Christos Chrysafis, Ben Collins, Scott Dugas, Jay Dunkelberger, Moussa Ehsan, Scott Gray, Alec Grieser, Ori Herrnstadt, Kfir Lev-Ari, Mike McMahon, Nicholas Schiefer, Alexander Shraer
SIGMOD Conference7