Data Model

Relational

Hardware Acceleration

RDMA

Indexes

Not Supported

Joins

Nested Loop Join Hash Join Sort-Merge Join

Yellowbrick supports hash, sort-merge, and nested loop joins.

Query Compilation

Code Generation

Yellowbrick partitions query plans into segments and converts them into C++ code. Segments are then compiled into machine code in parallel using a modified version of LLVM which is memory-resident with its ASTs pre-loaded. Compiled object files are cached and reused.

Query Execution

Vectorized Model

Query Interface

SQL

Storage Architecture

Hybrid

Storage Model

Hybrid

Stored Procedures

Supported

Yellowbrick supports PL/pgSQL stored procedures (CREATE PROCEDURE) but not user-defined functions (CREATE FUNCTION). Unlike in PostgreSQL, stored procedures in Yellowbrick can return values and be called from SELECT statements, but only when there is no table-referencing FROM clause.

Triggers are not supported.

System Architecture

Shared-Nothing

Yellowbrick Logo
Website

https://yellowbrick.com

Tech Docs

https://yellowbrick.com/docs/

Twitter

@YellowbrickData

Developer

Yellowbrick Data

Country of Origin

US

Start Year

2014

Project Type

Commercial

Written in

C, C++, Go, Java, Python

Derived From

PostgreSQL

Compatible With

PostgreSQL

Operating Systems

Hosted, Linux

Licenses

Proprietary

Wikipedia

https://en.wikipedia.org/wiki/Yellowbrick_Data