DBMS > Amazon Redshift vs. BigObject vs. Brytlyt vs. MonetDB vs. SurrealDB

System Properties Comparison Amazon Redshift vs. BigObject vs. Brytlyt vs. MonetDB vs. SurrealDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for real-time computations and queries

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

A relational database management system that stores data in columns

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Document store
Graph DBMS

Secondary database models

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

docs.bigobject.io

docs.brytlyt.io

www.monetdb.org/Documentation

surrealdb.com/docs

Developer

Amazon (based on PostgreSQL)

BigObject, Inc.

Brytlyt

MonetDB BV

SurrealDB Ltd

Initial release

2012

2015

2016

2004

2022

Current release

5.0, August 2023

Dec2023 (11.49), December 2023

v1.5.0, May 2024

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

Mozilla Public License 2.0

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++ and CUDA

Rust

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

yes

SQL 2003 with some extensions

SQL-like query language

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

user defined functions

in PL/pgSQL

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

automatically between fact table and dimension tables

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

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