DBMS > EXASOL vs. Faircom EDGE vs. OrientDB vs. RisingWave vs. Snowflake

System Properties Comparison EXASOL vs. Faircom EDGE vs. OrientDB vs. RisingWave vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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)

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

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

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

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	0.64
Rank	#238	Overall
	#110	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.exasol.com

www.faircom.com/products/faircom-edge

orientdb.org

www.risingwave.com/database

www.snowflake.com

Technical documentation

www.exasol.com/resources

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

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

docs.risingwave.com/docs/current/intro

docs.snowflake.net/manuals/index.html

Developer

Exasol

FairCom Corporation

OrientDB LTD; CallidusCloud; SAP

RisingWave Labs

Snowflake Computing Inc.

Initial release

2000

1979

2010

2022

2014

Current release

V3, October 2020

3.2.29, March 2024

1.2, September 2023

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache version 2

Open Source

Apache Version 2.0

commercial

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

Rust

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

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

Docker
Linux
macOS

hosted

Data scheme

yes

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

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

yes

Standard SQL-types and JSON

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

yes

SQL

Support of SQL

yes

ANSI SQL queries

SQL-like query language, no joins

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

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

JDBC
PostgreSQL wire protocol

CLI Client
JDBC
ODBC

Supported programming languages

Java
Lua
Python
R

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

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

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

.Net, JavaScript, C/C++

Java, Javascript

UDFs in Python or Java

user defined functions

Triggers

yes

Hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

relationship in graphs

yes

Transaction concepts

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

ACID

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

Access rights for users, groups and roles 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

Users and Roles

Users with fine-grained authorization concept, user roles and pluggable authentication

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