DBMS > 4D vs. HEAVY.AI vs. LevelDB vs. Snowflake

System Properties Comparison 4D vs. HEAVY.AI vs. LevelDB vs. Snowflake

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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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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

Primary database model

Relational DBMS

Key-value 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	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.4d.com

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

github.com/google/leveldb

www.snowflake.com

Technical documentation

developer.4d.com

docs.heavy.ai

github.com/google/leveldb/blob/main/doc/index.md

docs.snowflake.net/manuals/index.html

Developer

4D, Inc

HEAVY.AI, Inc.

Google

Snowflake Computing Inc.

Initial release

1984

2016

2011

2014

Current release

v20, April 2023

5.10, January 2022

1.23, February 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

BSD

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

C++

Server operating systems

OS X
Windows

Linux

Illumos
Linux
OS X
Windows

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

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

close to SQL 92

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC
Thrift
Vega

CLI Client
JDBC
ODBC

Supported programming languages

4D proprietary IDE
PHP

All languages supporting JDBC/ODBC/Thrift
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

none

Sharding

Round robin

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

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

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

with automatic compression on writes

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

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

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