DBMS > HEAVY.AI vs. OpenEdge vs. SiriDB vs. Snowflake

System Properties Comparison HEAVY.AI vs. OpenEdge vs. SiriDB vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

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

Application development environment with integrated database management system

Open Source Time Series DBMS

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

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

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

www.progress.com/openedge

siridb.com

www.snowflake.com

Technical documentation

docs.heavy.ai

documentation.progress.com/output/ua/OpenEdge_latest

docs.siridb.com

docs.snowflake.net/manuals/index.html

Developer

HEAVY.AI, Inc.

Progress Software Corporation

Cesbit

Snowflake Computing Inc.

Initial release

2016

1984

2017

2014

Current release

5.10, January 2022

OpenEdge 12.2, March 2020

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

MIT License

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

Linux

AIX
HP-UX
Linux
Solaris
Windows

Linux

hosted

Data scheme

yes

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

Typing

predefined data types such as float or date

yes

Numeric data

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

JDBC
ODBC
Thrift
Vega

JDBC
ODBC

HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

Progress proprietary ABL (Advanced Business Language)

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

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

Sharding

Round robin

horizontal partitioning

since Version 11.4

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

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

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

fine grained access rights according to SQL-standard

Users and groups

simple rights management via user accounts

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

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