# Datastores

Published articles for Datastores.

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## Seeing is believing: a client-centric specification of database isolation

DevFeed: [Seeing is believing: a client-centric specification of database isolation](<https://devfeed.tech/articles/seeing-is-believing-a-client-centric-specification-of-database-isolation-28593.md>)

Original publisher: [Read original article](<https://blog.acolyer.org/2020/11/30/seeing-is-believing/>)

Author: adriancolyer

Published: 2020-11-30T14:08:00Z

Content type: opinion

Language: en

Sources: [Adrian Colyer](<https://devfeed.tech/sources/adrian-colyer.md>)

Topics: [Database](<https://devfeed.tech/topics/database.md>), [systems](<https://devfeed.tech/topics/systems.md>)

Tags: [database](<https://devfeed.tech/tags/database.md>), [datastores](<https://devfeed.tech/tags/datastores.md>), [paper](<https://devfeed.tech/tags/paper.md>), [state](<https://devfeed.tech/tags/state.md>), [storage](<https://devfeed.tech/tags/storage.md>), [uncategorized](<https://devfeed.tech/tags/uncategorized.md>), [visibility](<https://devfeed.tech/tags/visibility.md>)

### AI overview

This article reviews "Seeing is believing," a paper that proposes defining database isolation guarantees in terms of effects visible to clients. Its state-based formalization treats storage systems as black boxes and aims to clarify observable behavior for application developers while preserving implementation freedom.

### Source excerpt

Seeing is believing: a client-centric specification of database isolation, Crooks et al., PODC'17. Last week we looked at Elle, which detects isolation anomalies by setting things up so that the inner workings of the database, in the form of the direct serialization graph (DSG), can be externally recovered. Today's paper choice, 'Seeing is believing' also deals ... Continue reading Seeing is believing: a client-centric specification of database isolation

## Helios: hyperscale indexing for the cloud & edge - part 1

DevFeed: [Helios: hyperscale indexing for the cloud & edge - part 1](<https://devfeed.tech/articles/helios-hyperscale-indexing-for-the-cloud-edge-part-1-28588.md>)

Original publisher: [Read original article](<https://blog.acolyer.org/2020/10/26/helios-part-1/>)

Author: adriancolyer

Published: 2020-10-26T20:22:00Z

Content type: article

Language: en

Sources: [Adrian Colyer](<https://devfeed.tech/sources/adrian-colyer.md>)

Topics: [data-processing](<https://devfeed.tech/topics/data-processing.md>), [big-data](<https://devfeed.tech/topics/big-data.md>), [Cloud](<https://devfeed.tech/topics/cloud.md>), [distributed-systems](<https://devfeed.tech/topics/distributed-systems.md>), [data](<https://devfeed.tech/topics/data.md>), [Edge](<https://devfeed.tech/topics/edge.md>), [Microsoft](<https://devfeed.tech/topics/microsoft.md>), [client](<https://devfeed.tech/topics/client.md>), [servers](<https://devfeed.tech/topics/servers.md>)

Tags: [architecture](<https://devfeed.tech/tags/architecture.md>), [big-data](<https://devfeed.tech/tags/big-data.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [data](<https://devfeed.tech/tags/data.md>), [data-processing](<https://devfeed.tech/tags/data-processing.md>), [datastores](<https://devfeed.tech/tags/datastores.md>), [distributed](<https://devfeed.tech/tags/distributed.md>), [distributed-computing](<https://devfeed.tech/tags/distributed-computing.md>), [edge](<https://devfeed.tech/tags/edge.md>), [idc](<https://devfeed.tech/tags/idc.md>), [latency](<https://devfeed.tech/tags/latency.md>), [microsoft](<https://devfeed.tech/tags/microsoft.md>), [paper](<https://devfeed.tech/tags/paper.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [server](<https://devfeed.tech/tags/server.md>), [streams](<https://devfeed.tech/tags/streams.md>), [systems](<https://devfeed.tech/tags/systems.md>), [uncategorized](<https://devfeed.tech/tags/uncategorized.md>)

### AI overview

This first part of a discussion of Helios examines its role as a reference architecture for distributed big-data systems. It describes the pressures driving cloud platforms toward new approaches, including growing data volume, variable arrival rates, lower latency, reduced data-center costs, and stronger privacy considerations.

### Source excerpt

Helios: hyperscale indexing for the cloud & edge, Potharaju et al., PVLDB'20 On the surface this is a paper about fast data ingestion from high-volume streams, with indexing to support efficient querying. As a production system within Microsoft capturing around a quadrillion events and indexing 16 trillion search keys per day it would be interesting in its own right, ... Continue reading Helios: hyperscale indexing for the cloud & edge - part 1