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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Citus vs Greenplum Database

Citus vs Greenplum Database

OverviewComparisonAlternatives

Overview

Citus
Citus
Stacks60
Followers124
Votes11
GitHub Stars12.0K
Forks736
Greenplum Database
Greenplum Database
Stacks47
Followers111
Votes0
GitHub Stars6.2K
Forks1.7K

Citus vs Greenplum Database: What are the differences?

Key Differences between Citus and Greenplum Database

Citus and Greenplum Database are both distributed databases that provide scalability and high-performance for handling large volumes of data. However, there are several key differences between these two databases.

  1. Architecture: Citus is built on top of PostgreSQL and extends it with a distributed architecture that allows it to horizontally scale across multiple nodes. On the other hand, Greenplum Database is based on the PostgreSQL project but includes a parallel query engine that enables it to process large datasets in a distributed manner.

  2. Data Distribution: Citus uses sharding to distribute data across multiple nodes in a cluster. It partitions the data based on a configurable shard key, allowing queries to be executed in parallel on different shards. In contrast, Greenplum Database uses a concept called the "interleaved sort key" to distribute data across segments. This allows for efficient data retrieval as segments can be accessed in parallel.

  3. Query Execution: Citus leverages query-aware sharding to optimize query execution. It pushes down certain operations to individual shards and performs query coordination at the coordinator node, reducing data movement and improving performance. Greenplum Database, on the other hand, employs a massively parallel processing (MPP) approach where queries are divided into smaller tasks that are executed in parallel across segments.

  4. Workload Management: Citus provides automatic workload management that dynamically adjusts the number of shards a query runs on based on available resources. This ensures that queries are efficiently distributed and utilize the cluster's resources optimally. Greenplum Database also offers workload management capabilities through its Query Resource Manager (QRM) that allows administrators to allocate system resources to different queries and users.

  5. Data Types: Citus supports most of the PostgreSQL data types and extensions, making it compatible with existing applications. Greenplum Database, on the other hand, has its own set of data types and functions, which may require some modifications to existing applications when migrating.

  6. Community and Support: Citus is an open-source extension to PostgreSQL and benefits from the vibrant PostgreSQL community. It also offers enterprise support through a paid subscription. Greenplum Database is a commercially-supported product with a dedicated support team from the parent company.

In Summary, while both Citus and Greenplum Database are distributed databases that provide scalability and high-performance, they differ in terms of architecture, data distribution, query execution, workload management, data types, and community and support.

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Detailed Comparison

Citus
Citus
Greenplum Database
Greenplum Database

It's an extension to Postgres that distributes data and queries in a cluster of multiple machines. Its query engine parallelizes incoming SQL queries across these servers to enable human real-time (less than a second) responses on large datasets.

It is a massively parallel processing (MPP) database server with an architecture specially designed to manage large-scale analytic data warehouses and business intelligence workloads. It is based on PostgreSQL open-source technology.

Multi-Node Scalable PostgreSQL;Built-in Replication and High Availability;Real-time Reads/Writes On Multiple Nodes;Multi-core Parallel Processing of Queries;Tenant isolation
Core SQL Conformance; MPP Architecture; Innovative Query Optimization; Polymorphic Data Storage; Integrated In-Database Analytics
Statistics
GitHub Stars
12.0K
GitHub Stars
6.2K
GitHub Forks
736
GitHub Forks
1.7K
Stacks
60
Stacks
47
Followers
124
Followers
111
Votes
11
Votes
0
Pros & Cons
Pros
  • 6
    Multi-core Parallel Processing
  • 3
    Drop-in PostgreSQL replacement
  • 2
    Distributed with Auto-Sharding
No community feedback yet
Integrations
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Java
Java
Rails
Rails
Datadog
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Logentries
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Heroku
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Papertrail
Papertrail
PostgreSQL
PostgreSQL
PostgreSQL
PostgreSQL
Kong
Kong
Slick
Slick
Heroku
Heroku
Apache Hive
Apache Hive
Clever Cloud
Clever Cloud
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Couchbase
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Sails.js
Sails.js
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Metabase

What are some alternatives to Citus, Greenplum Database?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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