How is Citus different than PostgreSQL; what does it provide in addition to manually sharded PostgreSQL?
Citus extends PostgreSQL to support distributed SQL queries. On top of PostgreSQL, Citus comes with its own transparent sharding, replication, distributed query planner and executor logic which enable execution of distributed SQL queries in parallel. This provides Hadoop-like fault tolerance, scalability and recovery from mid-query failures while allowing large datasets to be queried orders of magnitude faster than what has been possible on PostgreSQL before.
Which PostgreSQL versions are compatible with Citus?
Citus Version Compatible with PostgreSQL 5.2 9.5 only 6.x 9.5, 9.6 7.x 9.6, 10
Do you support all PostgreSQL features and the SQL standard?
Since Citus provides distributed functionality by extending PostgreSQL, it uses the standard PostgreSQL SQL constructs. It provides full SQL support for queries which access a single node in the database cluster. These queries are common, for instance, in multi-tenant applications where different nodes store different tenants (see When to Use Citus).
Will Citus work with my current PostgreSQL extensions, tools and drivers?
Since Citus is based on PostgreSQL, you can directly use PostgreSQL extensions such as HyperLogLog, TopN, or PostGIS with it. When using other extensions, you will first need to create the Citus extension on your PostgreSQL instance and then the other extensions you want to use. Citus will work with tools that use standard PostgreSQL drivers such as Tableau through regular ODBC/JDBC drivers. In general, you can use standard PostgreSQL drivers and language bindings with Citus, which means almost any language is supported. You can view a list of supported drivers and interfaces for PostgreSQL here.
Who are your customers? What do they use Citus for?
You can find a subset of our customers listed in our homepage and examples of what Citus is used for under our published case studies. Stay tuned as we work on sharing more examples of Citus deployments publicly! Currently Citus is used by many companies ranging from Silicon Valley startups to publicly listed corporations and in sectors including web & mobile analytics, digital marketing, web infrastructure, security, advertising technology, retail, digital media, etc... Our customers process billions of events in real-time on their Citus clusters while continuing to use the PostgreSQL features and extensions they're familiar with.
What is the biggest Citus deployment in terms of data size and number of nodes?
Citus deployments continue scaling up horizontally as we speak. On the last count, we had customers keeping hundreds of TBs on Citus, using tens of nodes in parallel and ingesting TBs of data per day. We test Citus on 100+ nodes and Citus is capable of keeping and processing PB scale workloads so we look forward to the continuing growth of our customers' Citus deployments.
How is Citus different than other analytics databases?
Citus extends, rather than forks, PostgreSQL. Therefore, you have access to the features, tools and extensions that come with the latest version of PostgreSQL. Citus is optimized for scaling multi-tenant applications and for real-time analytics workloads. It brings together fast parallel query execution with real-time data ingestion and high concurrency capabilities.
You can deploy Citus on our managed Citus Cloud platform, or on-premises depending on your preferences.
Is Citus a columnar database?
Citus is not a columnar database by design since it extends PostgreSQL. However, it can be used in combination with the cstore_fdw extension, which gives Citus the capability to create distributed columnar tables. This helps to reduce the data footprint and improves the performance for disk-bound workloads.
How fast is Citus?
Citus effectively parallelizes queries and achieves orders of magnitude faster execution compared to vanilla PostgreSQL through simultaneous utilization of multiple cores available in your cluster of servers. Citus enables human real-time interaction (seconds) with large datasets that span billions of records. Watch our demo to see how Citus speeds up PostgreSQL.
Is Citus able to parallelize query execution on a single node, or does that require multiple nodes?
A single Citus node stores multiple shards of the same distributed table. This enables Citus to use multiple cores for a single query by virtue of hitting multiple PostgreSQL tables (shards) on each node. However, to get true scalability in performance and reliability, we recommend a multi-node cluster. In cases where queries hit the disk, a single node setup can easily become disk I/O bound.
Can I deploy Citus on premises or on the cloud?
You can deploy Citus on premises or on the cloud. Go here to try it out.
What uptime does Citus Cloud provide?
If you require higher uptime for you application you can enable high availability. With high availability turned on we run a standby which receives streaming updates and in the event of a failure we automatically fail you over. Rough guidance would be that without high availability a recovery could take about an hour per 100 GB. With high availability the timespan is closer to minutes.
With Citus do I still need to backup my database? How do I deal with hardware failures?
Citus replicates data for fault tolerance on the worker nodes, see our documentation for failure semantics. The Citus master node contains only metadata, and we recommend using a standard PostgreSQL backup / replication tool to provide high availability and reliability, such as streaming replication.
How many nodes do I need for every 500GB of data?
The number of nodes needed depends on the use-case and performance requirements. Citus architecture scales out processing power, memory and storage linearly, and you can read more about its performance characteristics here.
How do I manage sharding? Do I do it at the application layer?
Citus provides transparent sharding at the database layer, thus allowing users to keep their applications unchanged. See more about the Citus architecture and sharding semantics.
How do I optimize the shard count on my cluster?
Optimal shard count is related to the total number of cores on the workers. Citus partitions an incoming query into its fragment queries which run on individual worker shards. Hence, the degree of parallelism for each query is governed by the number of shards the query hits. To ensure maximum parallelism, you should create enough shards on each node such that there is at least one shard per CPU core.
Is it easy to move from PostgreSQL to Citus? How about from MySQL?
Migrating an existing relational store to Citus sometimes requires adjusting the schema and queries for optimal performance. Since Citus is deployed as a PostgreSQL extension, PostgreSQL users can often start using Citus by simply installing the extension on their existing database. Once the extension is created, you can create and use distributed tables through standard PostgreSQL interfaces while maintaining compatibility with existing PostgreSQL tools. For more information, see our guide to Transitioning to Citus.
If you are moving from MySQL or any other relational database, the migration path is similar to moving to PostgreSQL from another relational database. We've had numerous customers move from MySQL to Citus with little change in their applications.
How does cstore_fdw work with Citus?
Citus treats cstore_fdw tables just like regular PostgreSQL tables. When cstore_fdw is used with Citus, each logical shard is created as a foreign cstore_fdw table instead of a regular PostgreSQL table. If your cstore_fdw use case is suitable for the distributed nature of Citus (e.g. large dataset archival and reporting), the two can be used to provide a powerful tool which combines query parallelization, seamless sharding and HA benefits of Citus with superior compression and I/O utilization of cstore_fdw.
What happened to pg_shard?
With the open-source release of Citus v5.x, pg_shard's codebase has been merged into Citus to offer you a unified solution which provides the advanced distributed query planning previously only enjoyed by CitusDB customers while preserving the simple and transparent sharding and real-time writes and reads pg_shard brought to the PostgreSQL ecosystem. Our flagship product, Citus, provides a superset of the functionality of pg_shard and we have migration steps to help existing users to perform a drop-in replacement. Please contact us for more information.
How much does Citus cost?
Citus Community edition is open source and free for download here. You can find our pay-as-you-go pricing for the Citus Cloud database online. We have several different pricing models for our Citus Enterprise offering including OEM, site-wide, and per-node licenses. Please contact sales for more details.
How do I license Citus Data Products?
The Citus server is licensed under the GNU Affero General Public License v3.0. For additional details, including answers to common questions about the AGPL, see the FAQ from the Free Software Foundation. The client drivers are licensed under the PostgreSQL license.
With this licensing structure, we looked to accomplish the following objectives:
- Allow users to download Citus, see the source code, and use it for free.
- Require users who choose to modify Citus to fit their needs, to release the patches to the software development community.
- Require users who are unwilling to release the patches to the software development community to purchase a commercial license.
With a significant volume of database software delivered today as a hosted service vs. distributed in binary form, GNU AGPL became the most effective license to fulfill all of the above.
Having the client drivers under the PostgreSQL license removes any ambiguity as to the extent of the server license. We also have the Citus Enterprise product available under a commercial license from Citus Data.