Enterprise Customer Data Platform - Treasure Data Blog - Part 24

How to Succeed at Importing XML to Just About Anywhere (without converting to JSON first)

JSON is everywhere. Nowadays, almost any emerging data ingestion framework or REST API endpoint uses JSON as a data transfer format. In fact, many will argue that since data is stored in records and array...

February 28, 2016

Elastic 2016 and Fluentd FAQs

Fluentd at {ON} ‘16 Last week, Elastic, the company behind Elasticsearch, Logstash, Kibana and Beats, put together their annual user conference in San Francisco. Because Elasticsearch is a popular backend for Fluentd, the...

February 25, 2016

451 Revisits Treasure Data: What’s Changed This Year

A year ago, analysts at 451 Research took a close look at Treasure Data. Now, they've come back to see what's changed. Since the data science space is constantly evolving, analysts are imperative to helping navigate the field. James Curtis of 451 dives into what Treasure Data is today, and how we...

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...

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