---
title: "#189: How Netflix Scale Their Time Series Data Storage Architecture"
publication: "DB Weekly"
issue: 189
published_at: "2018-02-02"
canonical_url: "https://dbweekly.com/issues/189"
---

Database Weekly 189   

This week's database news -[Read this on the Web](http://dbweekly.com/issues/189) 

[Database Weekly](http://dbweekly.com) Issue 189 — February 2, 2018     

[Advanced SQL: Common Table Expressions](http://mjk.space/advanced-sql-cte/) — The latest in a series discussing advanced SQL concepts in the context of how they improve more elementary SQL. This time, temporary in-query tables in the form of common table expressions (CTE). Michal Konarskitutorial [Scaling Time Series Data Storage at Netflix](https://medium.com/netflix-techblog/scaling-time-series-data-storage-part-i-ec2b6d44ba39) — How the video streaming service has evolved a time series data storage architecture through multiple jumps in scale. Duvedi, Li, Garg, and Fisher-Ogdenstory [SelectStar: Turn Database Monitoring Information Into Insight](https://selectstar.io/better-insights/?utm_source=CooperPress&utm_medium=Primary&utm_campaign=Database+Weekly+Primary+Link+Feb2) — SelectStar is the only database monitoring solution that digs into today’s modern data tier to provide recommendations, including those that may increase query speeds. Like what you see? You can take action immediately with a single click. SelectStarsponsored [![\](https://copm.s3.amazonaws.com/114ff587.png)](https://selectstar.io/better-insights/?utm_source=CooperPress&utm_medium=Primary&utm_campaign=Database+Weekly+Primary+Link+Feb2) [Our Newest Newsletter: MongoDB Weekly](https://mongodb.email/) — We’re covering the vast ecosystem around the most popular non-relational NoSQL database. Check out [this sample issue.](https://mongodb.email/issues/1) Cooperpressnews [Building a Fast Data Ingestion Pipeline to Redshift](https://blend.com/redshifting-into-gear/) — A data team built out a data ingestion pipeline for loading data from S3 into Amazon Redshift. Over a week, they increased its performance 1000x - here's the story of how. Alex Fish and Jason Ngstory [Hazelcast In-Memory Data Grid Now for Go Developers Too](https://blog.hazelcast.com/hazelcast-go-getters/) — Go now has [an official client](https://hazelcast.org/clients/go/) for [Hazelcast](https://hazelcast.org/), a popular, open source JVM-based in-memory data grid. Neil Stevensontutorial [Building a Full-Text Search App Using Docker and Elasticsearch](https://blog.patricktriest.com/text-search-docker-elasticsearch/) — A thorough tutorial that brings three key technologies together: Node.js, Docker, and the Elasticsearch document database. Patrick Triesttutorial [Fishing for Graphs in a Hadoop Data Lake](https://www.oreilly.com/ideas/fishing-for-graphs-in-a-hadoop-data-lake) — Exploring many small regions of a graph at low latency using specialized graph & multi-model databases. Max Neunhöffertutorial [Citus 7.2: Distributed Postgres W/ CTEs, Complex Subqueries, Set Operations, and More](https://www.citusdata.com/blog/2018/01/26/citus-7-2-ctes-complex-subqueries-set-operations/) — The Citus 7.2 extension to Postgres now includes distributed database features such as expanded support for distributed SQL and the distribution of complex subqueries across multiple nodes, and more. citusdatanews [MongoDB Is Now Available in All Google Cloud Regions Via Atlas](https://www.mongodb.com/blog/post/new-to-mongodb-atlas-availability-across-all-google-cloud-platform-regions?jmp=cpress&utm_campaign=WW_CP_newsletter_sponsorship_FY19Q1&utm_content=brief&utm_medium=display&utm_source=dbweekly&utm_date=20180202) mongodbsponsored news [How the Citus Distributed Database Rebalances Data](https://www.citusdata.com/blog/2018/02/01/how-citus-database-rebalances-your-data/) — Citus is an extension for scaling Postgres horizontally. citusdatatutorial [How Smelly are Your (Database) Relations?](http://www.tusharma.in/research/smelly-database-relations/) Tushar Sharmatutorial [Tuning MySQL: 3 Simple Tweaks](https://medium.com/@richb_/tuning-mysql-3-simple-tweaks-6356768f9b90) Rich Barretttutorial [Calculating a Customer's Lifetime Value with SQL](https://statsbot.co/blog/calculating-customer-lifetime-value-sql-example/) Luba Belokontutorial [Optimising Graph Lookups in MongoDB](https://medium.com/dbkoda/optimising-graph-lookups-in-mongodb-49483afb55c8) Guy Harrisontutorial [SQL Server 2017 on Linux Webcast Series](https://blogs.technet.microsoft.com/dataplatforminsider/2018/01/22/sql-server-2017-on-linux-webcast-series/) — You have to register but they’ll all on demand now. Microsoftvideo [Use SQL in MongoDB? Of Course You Can. We'll Show You How](https://studio3t.com/download/?utm_source=Newsletter&utm_medium=DBWeekly&utm_campaign=Jan2018) Studio 3Tsponsored [5 Real World Uses for Redis](https://ryanmccue.ca/5-real-world-uses-for-redis/) Ryan McCuetutorial [Supporting Operational Systems in a Big Data World](https://www.databasejournal.com/features/db2/supporting-operational-systems-in-a-big-data-world.html) Lockwood Lyontutorial [PostgreSQL's Hidden Gems](http://www.craigkerstiens.com/2018/01/31/postgres-hidden-gems/) Craig Kerstiensopinion [fx: A Command-Line JSON Processing Tool](https://github.com/antonmedv/fx) Anton Medvedevcode    

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