If you’re looking at Citus it’s likely you’ve outgrown a single node database. In most cases your application is no longer performing as you’d like. In cases where your data is still under 100 GB a single Postgres instance will still work well for you, and is a great choice. At levels beyond that Citus can help, but how you model your data has a major impact on how much performance you’re able to get out of the system.
Since Postgres started supporting NoSQL (via hstore, json, and jsonb), the question of when to use Postgres in relational mode vs NoSQL mode has come up a lot. Do you entirely abandon traditional table structures, and go with documents all the way? Or do you intermingle both? The answer unsurprisingly is: it depends. Each newer model including hstore, JSON, and JSONB has their ideal use cases. Here we’ll dig deeper into each and see when you should consider using them.
At Citus we want to enable you to build real-time applications across large amounts of data with ease. One part of that is Citus makes it simple for you to shard your data and use scale-out capabilities to leverage all your processing power. Another part is Citus Cloud: our managed, hosted offering of Citus running on AWS.
Today taking advantage of Citus becomes even easier with Citus Cloud going into general availability. You can read on to discover what’s included with Citus Cloud or sign-up to get started right away.
PG Conf Silicon Valley is happening again this year in November and we’re looking to make it even better and more informative than last year. To do that we’re looking to you, both as an attendee and to come speak. We’ve already received a lot of great...
PostgreSQL is known for its great extensibility and powerful plugins. One particular category of extensions is Foreign Data Wrappers or FDWs. FDWs allow us to interact from within Postgres directly with other data stores such as hdfs, columnar stores, mysql, etc. Combined with Citus’ scalability features, we can even leverage them to help us scale out those data stores where might otherwise be quite difficult.
At Citus we want to make dealing with large amounts of operational and analytical workloads easier. Data ingestion speed is key, being the necessary first step in working with any new database. Moreover ingestion is something you’ll do repeatedly in testing and development so the bulk-loading user experience is important as well. With the release of Citus 5.1 the experience in loading data is much better all around, and we’ve managed to sneak in a few other improvements as well. Read more below or give it a try today.
Product search is a common, yet sometimes challenging use-case for online retailers and marketplaces. It typically involves a combination of full-text search and filtering by attributes which differ for every product category. More complex use-cases may have many sellers that offer the same product, but with a different price and different properties.
At Citus we believe in making databases easier. Key to that is empowering users to scale Postgres beyond the typical limits of a single node. Our latest Citus release makes it easier than ever to scale memory and processors while retaining access to familiar SQL queries and rich Postgres features. But database management can be tricky even in the single-node case, so we at Citus have been hard at work building the next step in our journey to make databases easier: Citus Cloud, an on-demand cloud service on top of Amazon Web Services available today in private beta.
The following post is contributed by 8Kdata
An introduction to pg_paxos
Pg_paxos is a database level implementation of the widely renowned Paxos protocol, invented by Leslie Lamport. Pg_paxos offers a master-less (or multi-master, if you prefer) layer that can be enabled directly in the database without the need for external tools or transaction managers.
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