DBMS > ArcadeDB vs. Netezza vs. RisingWave vs. Snowflake

System Properties Comparison ArcadeDB vs. Netezza vs. RisingWave 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

Data warehouse and analytics appliance part of IBM PureSystems

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

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

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	7.56
Rank	#48	Overall
	#31	Relational DBMS

Score	0.61
Rank	#237	Overall
	#111	Relational DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

arcadedb.com

www.ibm.com/products/netezza

www.risingwave.com/database

www.snowflake.com

Technical documentation

docs.arcadedb.com

docs.risingwave.com/docs/current/intro

docs.snowflake.net/manuals/index.html

Developer

Arcade Data

IBM

RisingWave Labs

Snowflake Computing Inc.

Initial release

2021

2000

2022

2014

Current release

September 2021

1.2, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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

Java

Rust

Server operating systems

All OS with a Java VM

Linux

included in appliance

Docker
Linux
macOS

hosted

Data scheme

schema-free

yes

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

Typing

predefined data types such as float or date

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

SQL-like query language, no joins

yes

APIs and other access methods

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

JDBC
ODBC
OLE DB

JDBC
PostgreSQL wire protocol

CLI Client
JDBC
ODBC

Supported programming languages

Java

C
C++
Fortran
Java
Lua
Perl
Python
R

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

UDFs in Python or Java

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

yes

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

Users with fine-grained authorization concept

Users and Roles

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

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