DBMS > 4D vs. HEAVY.AI vs. Microsoft Azure Cosmos DB vs. Snowflake

System Properties Comparison 4D vs. HEAVY.AI vs. Microsoft Azure Cosmos DB vs. Snowflake

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Globally distributed, horizontally scalable, multi-model database service

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

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.4d.com

github.com/heavyai/heavydb
www.heavy.ai

azure.microsoft.com/services/cosmos-db

www.snowflake.com

Technical documentation

developer.4d.com

docs.heavy.ai

learn.microsoft.com/azure/cosmos-db

docs.snowflake.net/manuals/index.html

Developer

4D, Inc

HEAVY.AI, Inc.

Microsoft

Snowflake Computing Inc.

Initial release

1984

2016

2014

Current release

v20, April 2023

5.10, January 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

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

C++ and CUDA

Server operating systems

OS X
Windows

Linux

hosted

Data scheme

yes

schema-free

yes

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

Typing

predefined data types such as float or date

yes

JSON 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

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

close to SQL 92

yes

SQL-like query language

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC
Thrift
Vega

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

CLI Client
JDBC
ODBC

Supported programming languages

4D proprietary IDE
PHP

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

JavaScript

user defined functions

Triggers

yes

JavaScript

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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 and groups

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.