DBMS > Amazon Redshift vs. CockroachDB vs. Faircom EDGE vs. SurrealDB vs. SwayDB

System Properties Comparison Amazon Redshift vs. CockroachDB vs. Faircom EDGE vs. SurrealDB vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Document store
Graph DBMS

Key-value store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	5.73
Rank	#58	Overall
	#34	Relational DBMS

Score	0.09
Rank	#362	Overall
	#53	Key-value stores
	#155	Relational DBMS

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

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

aws.amazon.com/redshift

www.cockroachlabs.com

www.faircom.com/products/faircom-edge

surrealdb.com

swaydb.simer.au

Technical documentation

docs.aws.amazon.com/redshift

www.cockroachlabs.com/docs

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

surrealdb.com/docs

Developer

Amazon (based on PostgreSQL)

Cockroach Labs

FairCom Corporation

SurrealDB Ltd

Simer Plaha

Initial release

2012

2015

1979

2022

2018

Current release

24.1.0, May 2024

V3, October 2020

v1.5.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0, commercial license available

commercial

Restricted, free version available

Open Source

GNU Affero GPL V3.0

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

ANSI C, C++

Rust

Scala

Server operating systems

hosted

Linux
macOS
Windows

Android
Linux

ARM, x86
Raspbian
Windows

Linux
macOS
Windows

Data scheme

yes

dynamic schema

Flexible Schema (defined schema, partial schema, schema free)

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes, wire compatible with PostgreSQL

yes

ANSI SQL queries

SQL-like query language

APIs and other access methods

JDBC
ODBC

JDBC

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

Deno
Go
JavaScript (Node.js)
Rust

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

File partitioning

Customizable business rules for partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using RAFT

yes

Synchronous and asynchronous realtime replication based on transaction logs

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

when using SQL

Transaction concepts

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

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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

Role-based access control

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

yes, based on authentication and database rules

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