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postgresql: All content tagged as postgresql in NoSQL databases and polyglot persistence

Improvements in Rails 4 ActiveRecord for PostgreSQL

Kevin Faustino:

Out of all the supported databases available in Active Record, PostgreSQL received the most amount of attention during the development of Rails 4. In today’s countdown post, we are going to look at the various additions made to the PostgreSQL database adapter.

Teaser:

  1. hstore and hstore indexes support
  2. arrays
  3. uuid
  4. network address data types
  5. int4range, int8range
  6. json

Original title and link: Improvements in Rails 4 ActiveRecord for PostgreSQL (NoSQL database©myNoSQL)

via: http://blog.remarkablelabs.com/2012/12/a-love-affair-with-postgresql-rails-4-countdown-to-2013


PuppetDB: Configuration Management Database for Puppet

PuppetDB is replacing CouchDB for managing Puppet configurations and is a service layer written in Clojure with a PostgreSQL back-end. Not a graph database:

PuppetDB is a key component of the Puppet Data Library, and brings that to bear in its query API. Resources, facts, nodes, and metrics can all be queried over HTTP. For resources and nodes, there is a simple query language which can be used to form arbitrarily complex requests. The public API is the same one that Puppet uses to make storeconfigs queries (using the «||» operator) of PuppetDB, but provides a superset of the functionality provided by storeconfigs.

PuppetDB is faster, smarter, and has more complete data than ever before. […] PuppetDB offers great power over and insight into your infrastructure, and it’s only going to get bigger and better.

Original title and link: PuppetDB: Configuration Management Database for Puppet (NoSQL database©myNoSQL)

via: http://puppetlabs.com/blog/introducing-puppetdb-put-your-data-to-work/


MySQL Is Done. NoSQL Is Done. It's the Postgres Age

Jeff Dickey enumerates some of the new features available in PostgreSQL—schema-less data, array columns, queuing, full-text searching, geo-spatial indexing—concluding that PosgreSQL has now everything an application needs:

Postgres has taken the features out of all of these tools and integrate it right inside the platform. Now you don’t need to spin up a mongo cluster for non-rel data, rabbitmq cluster for queueing, solr box for searching. You can just have a single postgres server. That saves a huge ops headache since each of those clusters/boxes have to be durable, replicated, and scalable.

Sounds a bit too optimistic? As we’ve learned from the NoSQL space there are no silver bullets:

Now obviously, there’s a glaring downside with this approach: you get one box. Maybe a read slave or something, but really, you can’t scale it.

As you can imagine I disagree with most of the points, the only exception being that it is great to see so many useful features packaged with PostgreSQL—these are definitely going to make like easier for some of the developers.

But when talking about MySQL and NoSQL being done:

  1. MySQL is done, except it has a huge community, there are tons of developers very familiar with it, and last but not least MySQL powers massive deployments. This last part matters a lot.
  2. NoSQL is done, except many NoSQL solutions tackle different problem spaces providing optimal solutions for these by staying focused. Neither Oracle, nor MongoDB, nor PosgreSQL will be able to solve all problems. The wider range of problems they are covering, the less optimal solutions they are providing for corner case or extreme scenarios.

Original title and link: MySQL Is Done. NoSQL Is Done. It’s the Postgres Age (NoSQL database©myNoSQL)

via: http://dickey.xxx/mysql-is-done-it-s-the-postgres-age


Cassandra at Workware Systems: Data Model FTW

One of the stories in which the deciding factor for using Cassandra was primarily the data model and not its scalability characteristics:

We started working with relational databases, and began building things primarily with PostgreSQL at first.  But dealing with the kind of data that we do, the data model just wasn’t appropriate. We started with Cassandra in the beginning to solve one problem: we needed to persist large vector data that was updated frequently from many different sources. RDBMS’s just don’t do that very well, and the performance is really terrible for fast read operations. By contrast, Cassandra stores that type of data exceptionally well and the performance is fantastic. We went on from there and just decided to store everything in Cassandra.

Original title and link: Cassandra at Workware Systems: Data Model FTW (NoSQL database©myNoSQL)

via: http://www.datastax.com/2012/04/the-five-minute-interview-workware-systems


NoSQL and Relational Databases Podcast With Mathias Meyer

EngineYard’s Ines Sombra recorded a conversation with Mathias Meyer about NoSQL databases and their evolution towards more friendlier functionality, relational databases and their steps towards non-relational models, and a bit more on what polyglot persistence means.

Mathias Meyer is one of the people I could talk for days about NoSQL and databases in general with different infrastructure toppings and he has some of the most well balanced thoughts when speaking about this exciting space—see this conversation I’ve had with him in the early days of NoSQL. I strongly encourage you to download the mp3 and listen to it.

Original title and link: NoSQL and Relational Databases Podcast With Mathias Meyer (NoSQL database©myNoSQL)


Redis Persistence Demystified

TL;DR:

even if Redis is an in memory database it offers good durability compared to other on disk databases.

But you must read the post for all the nitty-gritty.

Original title and link: Redis Persistence Demystified (NoSQL database©myNoSQL)

via: http://antirez.com/post/redis-persistence-demystified.html


Induction: SQL? NoSQL? Explore, Query, Visualize

Matt Thompson‘s Induction is a free OS X application allowing access and visualization of data stored in PostgreSQL, MySQL, SQLite, Redis, and soon MongoDB.

Some are asking for a common NoSQL query language, some are trying to put a tabular format on top of NoSQL data, and some are building an indirection layer as a tool.

Original title and link: Induction: SQL? NoSQL? Explore, Query, Visualize (NoSQL database©myNoSQL)

via: http://inductionapp.com/


Jelastic Database Marketshare: MySQL, MongoDB, MariaDB

Jelastic, a company offering a cloud platform for Java server hosting, has published some stats about the databases used by their over 7000 users:

Jelastic Database Marketshare

While it would be wrong to generalize these results to absolute database marketshare, it is interesting nonetheless to see that MongoDB is already outrunning PostrgeSQL being the second most used database and that CouchDB, which was added only one month ago, is already used by 5% of Jelastic’s users. MySQL detains the first position with over 40% users or differently put double the number of the second place (MongoDB).

These numbers would be even more interesting if they would account for some real usage stats like database sizes or query volumes.

Mat Keep

Original title and link: Jelastic Database Marketshare: MySQL, MongoDB, MariaDB (NoSQL database©myNoSQL)

via: http://blog.jelastic.com/2012/01/23/database-marketshare-january-2012/