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What is Citus?

Citus enriches the widely appreciated Postgres experience by offering distributed table capabilities while being entirely open source. It now accommodates both schema-based and row-based sharding, ensuring compatibility with Postgres 16. You can effectively scale Postgres by distributing data and queries, starting with a single Citus node and smoothly incorporating additional nodes and rebalancing shards as your requirements grow. By leveraging parallelism, keeping a larger dataset in memory, boosting I/O bandwidth, and using columnar compression, query performance can be significantly enhanced, achieving speeds up to 300 times or even more. As an extension rather than a separate fork, Citus remains compatible with the latest Postgres versions, allowing you to leverage your existing SQL expertise and tools. Furthermore, it enables you to address infrastructure challenges by managing both transactional and analytical workloads within one database system. Available for free as open source, Citus allows for self-management while also inviting contributions to its development via GitHub. Transitioning your focus from database management to application development becomes easier as you run your applications on Citus within the Azure Cosmos DB for PostgreSQL environment, thus streamlining your workflow. This integration not only boosts efficiency but also empowers developers to harness the full potential of scalable, high-performance database solutions.

What is Apache Doris?

Apache Doris is a sophisticated data warehouse specifically designed for real-time analytics, allowing for remarkably quick access to large-scale real-time datasets. This system supports both push-based micro-batch and pull-based streaming data ingestion, processing information within seconds, while its storage engine facilitates real-time updates, appends, and pre-aggregations. Doris excels in managing high-concurrency and high-throughput queries, leveraging its columnar storage engine, MPP architecture, cost-based query optimizer, and vectorized execution engine for optimal performance. Additionally, it enables federated querying across various data lakes such as Hive, Iceberg, and Hudi, in addition to traditional databases like MySQL and PostgreSQL. The platform also supports intricate data types, including Array, Map, and JSON, and includes a variant data type that allows for the automatic inference of JSON data structures. Moreover, advanced indexing methods like NGram bloomfilter and inverted index are utilized to enhance its text search functionalities. With a distributed architecture, Doris provides linear scalability, incorporates workload isolation, and implements tiered storage for effective resource management. Beyond these features, it is engineered to accommodate both shared-nothing clusters and the separation of storage and compute resources, thereby offering a flexible solution for a wide range of analytical requirements. In conclusion, Apache Doris not only meets the demands of modern data analytics but also adapts to various environments, making it an invaluable asset for businesses striving for data-driven insights.

Media

Media

Integrations Supported

PostgreSQL
Algolia
Apache Flink
Apache Hive
Apache Spark
Azure Cosmos DB
CentOS
Cisco CX Cloud
ConvertFlow
Docker
Fedora
GitHub
Microsoft Azure
MixRank
PEX
Red Hat Cloud Suite
SelectDB
TapData
Ubuntu
VeloDB

Integrations Supported

PostgreSQL
Algolia
Apache Flink
Apache Hive
Apache Spark
Azure Cosmos DB
CentOS
Cisco CX Cloud
ConvertFlow
Docker
Fedora
GitHub
Microsoft Azure
MixRank
PEX
Red Hat Cloud Suite
SelectDB
TapData
Ubuntu
VeloDB

API Availability

Has API

API Availability

Has API

Pricing Information

$0.27 per hour
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Citus Data

Company Location

United States

Company Website

www.citusdata.com

Company Facts

Organization Name

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

doris.apache.org

Categories and Features

Categories and Features

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

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