by Mason Sharp | Jul 27, 2015 | Uncategorized |
The source code to Postgres-XL has now been changed from the Mozilla Public License to the more liberal PostgreSQL License. There is ongoing community work to merge PostgreSQL 9.5 into Postgres-XL, thanks to the contributions of 2ndQuadrant. The latest repository can be found here: git://git.postgresql.org/git/postgres-xl More updates will be coming...
by Mason Sharp | Jan 4, 2015 | Uncategorized |
Interested in using Postgres-XL with Docker? Matthieu Lagacherie and Yannick Drant have put together a docker container for testing: http://www.postmind.net/pgxl_docker-en.html
by Mason Sharp | Aug 7, 2014 | Uncategorized |
Come join us on August 12th to learn about Postgres-XL at the San Francisco Bay Area Meetup: SFPUG August: Postgres-XL Tuesday, Aug 12, 2014, 7:00 PM CloudFlare665 3rd Street, Suite 200 San Francisco, CA 81 PostgreSQL Users and Developers Attending Topic: Postgres-XL: Supersized PostgreSQLSpeaker: Mason SharpFood Sponsor: Translattice Inc.Host/Drink Sponsor: CloudFlare Inc.Location: TBD; Somewhere in San FranciscoPostgres-XL was recently released to further extend the open source Postgres ecosystem, allowing users to scale-out both transactional workloads and obtain fast response times… Check out this Meetup → Hope to see you...
by Mason Sharp | Aug 4, 2014 | Uncategorized |
You thought Postgres-XL was just a clustered solution? Postgres-XL works well on a single server for a data warehouse or reporting server. PostgreSQL is a fantastic multi-purpose database, but there is still no parallel query capability. What this means is, even if you have a 16 core server, your query is just going to use one single core while it processes that query, leaving the other 15 cores idle. Of course, if there are a lot of other concurrent sessions sharing resources, that may be acceptable. If there are very few, or automated reports that run, there are a lot of wasted resources. Instead, you could use Postgres-XL. Just install a GTM, a single coordinator, and multiple “datanodes” on the server, all running on different ports, and you have a one box cluster. Now when you submit a query to a coordinator, it will be parallelized and push down as much work as it can to the datanodes, getting more of those cores working and processing your queries faster. For even better performance, consider splitting the datanodes across multiple storage devices, instead of them contending for the same device. What about redundancy? You could setup each component to have a standby on another server, with a GTM standby, coordinator standby, and one datanode standby for each datanode on the primary server. Happy...
by Mason Sharp | Jun 15, 2014 | Uncategorized |
Satoshi Nagayasu put together a Chef cookbook for deploying Postgres-XL, found here in his blog: http://pgsnaga.blogspot.com/2014/06/deploying-postgres-xl-in-2-minutes-with.html Thank you,...
