DBMS > ArcadeDB vs. LeanXcale vs. OpenQM vs. Snowflake

System Properties Comparison ArcadeDB vs. LeanXcale vs. OpenQM vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

QpenQM is a high-performance, self-tuning, multi-value DBMS

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

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Key-value store
Relational DBMS

Multivalue DBMS

Relational DBMS

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

Score	0.02
Rank	#374	Overall
	#52	Document stores
	#38	Graph DBMS
	#56	Key-value stores
	#38	Time Series DBMS

Score	0.28
Rank	#286	Overall
	#41	Key-value stores
	#130	Relational DBMS

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

arcadedb.com

www.leanxcale.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.snowflake.com

Technical documentation

docs.arcadedb.com

docs.snowflake.net/manuals/index.html

Developer

Arcade Data

LeanXcale

Rocket Software, originally Martin Phillips

Snowflake Computing Inc.

Initial release

2021

2015

1993

2014

Current release

September 2021

3.4-12

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPLv2, extended commercial license available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

All OS with a Java VM

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

hosted

Data scheme

schema-free

yes

with some exceptions

yes

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

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

through Apache Derby

yes

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

CLI Client
JDBC
ODBC

Supported programming languages

Java

C
Java
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

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 can be defined down to the item level

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

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