As you probably already know, in MySQL 5.7.3 release, InnoDB Memcached reached a record of over 1 million QPS on a read only load. The overview of the benchmark and testing results can be seen in an earlier blog by Dimitri. In this blog, I will spend sometime on the detail changes we have made to achieve this number.
There’s another post detailing the benchmark:
The test was executed in “standalone” mode (both server and client are running on the same server). So, we used our biggest HW box we have in the LAB - a 48cores machine.
That’s a_good_ number. But if you think about it, the per-core QPS is not that high; if I remember correctly Redis can go up to 70k/s.
Original title and link: InnoDB Memcached plugin benchmark: 1mil QPS with in MySQL 5.7.3 ( ©myNoSQL)
Since announcing the GA couple of weeks ago, I’ve been noticing quite a few data related posts on the Google Compute Engine blog:
- Mon., 9th: DataStax Enterprise feels right at home in Google Compute Engine
- Tue., 10th: DataTorrent offers massive-scale, real-time stream analytics on Google Compute Engine
- Thu., 12th: Qubole helps you run Hadoop on Google Compute Engine
If you look at these, you’ll notice a theme: covering data from every angle; Cassandra/DSE from DataStax for OLTP, DataTorrent for stream processing, Qubole for Hadoop, MapR for their Hadoop-like solution. I can see this continuing for a while and making Google Compute Engine a strong competitor for Amazon Web Services.
One question remains though: will they be able to come up with a good integration strategy for all these 3rd party tools?
Original title and link: Google Compute Engine and Data ( ©myNoSQL)
The Rackspace post is titled “Choosing The Right Cloud Provider For Your MongoDB Database“, as they have a stake in the game. But the chart they’ve put together is generic enough to be useful whenever you have to decide where to host your database:
Original title and link: Choosing the right hosting for your database ( ©myNoSQL)
If you’ve never used Thrift (with or without HBase), the two articles authored by Jesse Anderson and posted on Cloudera’s blog will give you both a quick intro and
- How-to: Use the HBase Thrift Interface, Part 1: setting up, getting the language bindings, and connecting;
- How-to: Use the HBase Thrift Interface, Part 2: Inserting/Getting Rows: using HBase’s Thrift API from Python
Original title and link: An intro to HBase’s Thrift interface ( ©myNoSQL)
I have been trying to avoid graph “intro” slides and presentations.
There are only so many times you can stand to hear “…all the world is a graph…” as though that’s news. To anyone.
This presentation by Luca is different from the usual introduction to graphs presentation.
Original title and link: Why relationships are cool… Relationship in RDBMS vs graph databases ( ©myNoSQL)