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Items tagged replication in 2009

Filters: Year: 2009 × replication × Sorted by date


PostgreSQL 8.5alpha3 now available. “Hot Standby, allowing read-only connections during recovery, provides a built-in master-slave replication solution.” Woohoo! # 23rd December 2009, 9:57 am

Simple CouchDB multi-master clustering via Nginx. An impressive combination. CouchDB can be easily set up in a multi-master configuration, where writes to one master are replicated to the other and vice versa. This makes setting up a reliable CouchDB cluster is as simple as putting two such servers behind a single nginx proxy. # 19th November 2009, 4:37 pm

PostgreSQL 8.5 alpha 2 is out. “P.S. If you’re wondering about Hot Standby and Synchronous Replication, they’re still under heavy development and still (at this point) expected to be in 8.5.”—Hot Standby is PostgreSQL-speak for MySQL-style master/slave replication for scaling your reads. # 28th October 2009, 9:02 am

How We Made GitHub Fast. Detailed overview of the new GitHub architecture. It’s a lot more complicated than I would have expected—lots of moving parts are involved in ensuring they can scale horizontally when they need to. Interesting components include nginx, Unicorn, Rails, DRBD, HAProxy, Redis, Erlang, memcached, SSH, git and a bunch of interesting new open source projects produced by the GitHub team such as BERT/Ernie and ProxyMachine. # 21st October 2009, 9:14 pm

When I worked at Amazon.com we had a deeply-ingrained hatred for all of the SQL databases in our systems. Now, we knew perfectly well how to scale them through partitioning and other means. But making them highly available was another matter. Replication and failover give you basic reliability, but it’s very limited and inflexible compared to a real distributed datastore with master-master replication, partition tolerance, consensus and/or eventual consistency, or other availability-oriented features.

Matt Brubeck # 4th October 2009, 9:50 am

Londiste Tutorial. Master/slave replication for PostgreSQL, developed and used by Skype. # 9th September 2009, 11:06 pm

Keyspace. Yet Another Key-Value Store—this one focuses on high availability, with one server in the cluster serving as master (and handling all writes), and the paxos algorithm handling replication and ensuring a new master can be elected should the existing master become unavailable. Clients can chose to make dirty reads against replicated servers or clean reads by talking directly to the master. Underlying storage is BerkeleyDB, and the authors claim 100,000 writes/second. Released under the AGPL. # 16th July 2009, 10:30 am

PostgreSQL Development Priorities. The top two for 8.4 are “Simple built-in replication” and “Upgrade-in-place”, Josh Berkus is seeking feedback on priorities for future work on 8.5. # 28th May 2009, 8:08 pm

redis (via) An in-memory scalable key/value store but with an important difference: this one lets you perform list and set operations against keys, opening up a whole new set of possibilities for application development. It’s very young but already supports persistence to disk and master-slave replication. # 15th March 2009, 1:32 pm

[Drizzle] won’t be a get-out-of-jail-free card for very write-heavy applications but I bet it will do wonders for heavily replicated, heavily federated, read-heavy architectures (you know, normal stuff).

Richard Crowley # 8th March 2009, 6:05 pm

What happened to Hot Standby? Hot Standby (the ability to have read-only replication slaves) has been dropped from PostgreSQL 8.4 and is now scheduled for 8.5. “Making hard decisions to postpone features which aren’t quite ready is how PostgreSQL makes sure that our DBMS is ”bulletproof“ and that we release close to on-time every year”. # 8th March 2009, 9:28 am

Tokyo Tyrant Tutorial. Buried at the bottom of the Tokyo Tyrant protocol documentation, this is the best resource I’ve seen yet for getting up and running with the database server (including setting up replication). # 14th February 2009, 11:29 am

MemcacheDB. A server that speaks the memcache protocol but uses Berkeley DB for reliable persistent storage. Speedy: 20,000 writes/second and 60,000+ reads/second. Includes a full replication mechanism (with custom memcache protocol commands) based on Berkeley DB’s. # 5th January 2009, 12:37 pm