Matvey Arye

Software Developer at Timescale

About

Mat has been working on data infrastructure in both academia (Princeton, PhD) and industry. As one of TimescaleDB's core architects he works on performance, scalability, and query power. Previously, he attended Stuyvesant, The Cooper Union, and Princeton.

Matvey Arye has presented the following presentations

    Matvey Arye Performant Time-Series Storage and Continuously Up to Date Materialized Aggregates at Philly 2019

    presented by Matvey Arye

    Time-series workloads (i.e. data from sensors, IoT devices, finance, or even satellites) are one of the fasting growing segments of the database market, spreading across industries and use cases. Today, many developers working with time-series data turn to NoSQL databases for storage with scale, and relational databases for managing associated metadata and key business data, yet this leads to e...

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    Fri 19 2019 Dev
    Matvey Arye Gap Filling: Enabling New Analytic Capabilities in Postgres at Postgres Conference
    How Timescale’s open source extension increases the readability, performance, and efficiency of “gap-filling” queries.

    presented by Matvey Arye

    One property of real-time data is that it often arrives at irregular intervals. An example of this is minute-by-minute averages of temperature sensors where data arrives from a sensor that is intermittently offline.

    When querying such data, we often want results even for minutes that do not have data data reported from the sensor. In such cases, we often want data for such “gaps” reported ...

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    Thu 21 2019 Data
    Diana Hsieh Matvey Arye Andrew Staller Using TimescaleDB for time-series storage and analytics in Postgres at Silicon Valley
    An introduction to TimescaleDB, a Postgres extension, and use cases

    presented by Diana Hsieh, Matvey Arye, and Andrew Staller

    An Introductory Training on TimescaleDB

    TimescaleDB is an open-source time-series database, implemented as a Postgres extension, that improves insert rates by 20x over vanilla Postgres and offers much faster queries, while natively supporting full SQL (including JOINs). TimescaleDB achieves this by storing data on an individual server in a manner more common to...

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    Mon 15 2018 Dev
    Matvey Arye Performant time-series data management and analytics with Postgres at Silicon Valley

    presented by Matvey Arye

    Time-series databases are one of the fasting growing segments of the database market, spreading across industries and use cases. Common requirements including ingesting high volumes of structured data; answering complex, performant queries for both recent and historical time int...

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    Tue 16 2018 Data
    Matvey Arye Building a scalable time-series database on PostgreSQL at PGConf Local: Seattle [PgConf.US]
    TimescaleDB, packaged as a PostgresSQL extension

    presented by Matvey Arye

    Today everything is instrumented, generating more and more time-series data streams that need to be monitored and analyzed. When it comes to storing this data, many developers often start with some well-trusted system like PostgreSQL, but when their data hits a certain scale, give up its query power and ecosystem by migrating to some NoSQL or other "modern" time-series architecture. They face t...

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    Tue 14 2017 ops
    Matvey Arye Using PostgreSQL, Prometheus and Grafana for storing, analyzing and visualizing metrics at PostgresConf US 2018

    presented by Matvey Arye

    Grafana and Prometheus have become a popular duo for collecting, querying and graphing metrics, giving teams greater clarity on their operations. But while Prometheus has its own time-series storage subsystem specifically for metrics monitoring, many have found they require something for long-term, persistent storage that also allows more complex queries to be run across a larger dataset.

    In...

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