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28th May 2019 @ 10:00 am - 30th May 2019 @ 8:00 pm BST
Altinity is thrilled to be among the sponsors of the event. Meet our team at the Exhibit Hall
Use code “ALTINITY10” to get 10% off registration
1. ClickHouse Data Warehouse 101: The First Billion Rows
Speakers: Alexander Zaitsev, Altinity CTO; Robert Hodges, Altinity CEO
Thursday 2:55 PM – 3:45 PM @ Texas 6
Columnar stores like ClickHouse enable users to pull insights from big data in seconds, but only if you set things up correctly. This talk will walk through how to implement a data warehouse that contains 1.3 billion rows using the famous NY Yellow Cab ride data. We’ll start with basic data implementation including clustering and table definitions, then show how to load efficiently. Next we’ll discuss important features like dictionaries and materialized views, and how they improve query efficiency. We’ll end by demonstrating typical queries to illustrate the kind of inferences you can draw rapidly from a well-designed data warehouse. It should be enough to get you started–the next billion rows is up to you!
You can find the audio recording of this presentation here :
2. Opensource Column Store Databases: MariaDB ColumnStore vs. ClickHouse
Speaker: Alexander Rubin, Percona
Wednesday 11:00 AM – 11:50 AM, @ Texas 5
Running an analytical (OLAP) workload on top of MySQL can be slow and painful. A specifically designed storage format (“Column Store”) can significantly improve analytical queries’ performance. There are a number of opensource column store databases around. In this talk, I will focus on two of them which can support MySQL protocol: MariaDB ColumnStore and ClickHouse.
I will show some realtime benchmarks and use cases, and demonstrate how MariaDB ColumnStore and ClickHouse can be used for typical OLAP queries. I will also do a quick demo.
3. Beyond Relational Databases: A Look Into MongoDB, Redis, and ClickHouse
Speaker: Marcos Albe, Percona
Thursday 2:55 PM – 3:45 PM, @ Hill Country D
We all use and love relational databases… until we use them for purposes for which they are not a good fit: queues, caches, catalogs, unstructured data, counters, and many other use cases could be solved with relational databases, but are better solved with other alternatives.
In this talk, we’ll review the goals, pros and cons, and good and bad use cases of these alternative paradigms by looking at some modern open source implementations.
By the end of this talk, the audience will have learned the basics of three database paradigms (document, key-value, and columnar store) and will know when it’s appropriate to opt for one of these or when to favor relational databases and avoid falling into buzzword temptations.