DBMS > Amazon Redshift vs. BoltDB vs. Faircom EDGE vs. OrientDB vs. Postgres-XL

System Properties Comparison Amazon Redshift vs. BoltDB vs. Faircom EDGE vs. OrientDB vs. Postgres-XL

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Multi-model DBMS (Document, Graph, Key/Value)

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Relational DBMS

Key-value store

Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store

Relational 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	0.80
Rank	#215	Overall
	#31	Key-value stores

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

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

aws.amazon.com/redshift

github.com/boltdb/bolt

www.faircom.com/products/faircom-edge

orientdb.org

www.postgres-xl.org

Technical documentation

docs.aws.amazon.com/redshift

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

www.orientdb.com/docs/last/index.html

www.postgres-xl.org/documentation

Developer

Amazon (based on PostgreSQL)

FairCom Corporation

OrientDB LTD; CallidusCloud; SAP

Initial release

2012

2013

1979

2010

2014

since 2012, originally named StormDB

Current release

V3, October 2020

3.2.29, March 2024

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

Restricted, free version available

Open Source

Apache version 2

Open Source

Mozilla public license

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++

Java

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

Android
Linux

ARM, x86
Raspbian
Windows

All OS with a Java JDK (>= JDK 6)

Linux
macOS

Data scheme

yes

schema-free

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

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

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

XML type, but no XML query functionality

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

ANSI SQL queries

SQL-like query language, no joins

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC

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

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

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

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

yes

.Net, JavaScript, C/C++

Java, Javascript

user defined functions

Triggers

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

File partitioning

Customizable business rules for partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

Synchronous and asynchronous realtime replication based on transaction logs

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

when using SQL

yes

relationship in graphs

yes

Transaction concepts

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

ACID

yes

ACID

MVCC

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

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

Access rights for users and roles; record level security configurable

fine grained access rights according to SQL-standard

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