Treasure Data Blog | Analytics Infrastructure as a Service - Part 20

February 19, 2016

The Magic of Presto: Petabyte Scale SQL Queries in Seconds!

If you've been in the data analytics field for even a short period of time, you've probably at least heard of Spark, Hive or maybe Cloudera Impala as a means of running SQL-type queries against large semi-structured datasets. One you may not have heard about though, is Presto. Originally d...

February 17, 2016

Elasticsearch, and How to Make it Faster for ALL Queries

With millions of downloads since launch, Elasticsearch has become the open-source tool of choice for full text search. Also, it has become increasing popular for analytics use cases thanks to its ease of setup and JSON-based RESTful API. Like any other technology, however, Elasticsearch excels i...

February 16, 2016

Build a Simple Recommendation Engine with Hivemall and Minhash

This is a translation of this blog post, printed with permission from the author. In this post, I will introduce a technique called Minhash that is bundled in Treasure Data's Hivemall machine learning library. Minhash is not usually thought of as a machine learning technique, but as you will see...

February 11, 2016

Customer Highlight: Ingesting Massive Volumes of Data at Grindr

Treasure Data helps a mobile app company capture streaming data to Amazon Redshift Grindr was a runaway success. The first ever geo-location based dating app had scaled from a living room project into a thriving community of over 1 million hourly active users in under 3 years. The engineering t...

February 10, 2016

What’s the difference between Amazon Redshift and Aurora?

As you plan your analytics and data architecture on AWS, you may get confused between Redshift and Aurora. Both are advertised to be scalable and performant. Both are supposedly better than incumbents. Both have optically inspired names. So, what's the difference? In short, Redshift is OLAP where...

February 8, 2016

Raw SQL Access to Segment.com Data in Real-time

What's Segment? Segment is a cloud service that simplifies the process of integrating cloud services into your website and mobile apps. You can say it's a “tag management 2.0” tool to integrate multiple marketing and product management analytics tools with a single SDK. Once the raw data is flo...

February 3, 2016

Bringing Machine Learning to Elasticsearch with Logz.io and Treasure Data

Data analytics is a battle between order and chaos. As organizations build up their data infrastructure, we often see different, divergent pipelines sprouting up to accommodate respective needs. This leads to data silos as well as analytics silos: one team builds its own data pipeline for t...

February 1, 2016

Graduate from Mixpanel: Tracking Your Funnel Long Term

This post is part two of a two part series. Read part one here. As we saw with Part 1, we were able to create a funnel that allowed us to easily change the period of time and events that defined the funnel, and then visualize that funnel using R. However, like most business driven analytics, we w...

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