DBMS > AgensGraph vs. HEAVY.AI vs. Snowflake vs. TerminusDB

System Properties Comparison AgensGraph vs. HEAVY.AI vs. Snowflake vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Graph DBMS

Secondary database models

Spatial DBMS

Document store
RDF store

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

Score	0.16
Rank	#333	Overall
	#30	Graph DBMS
	#146	Relational DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	0.22
Rank	#323	Overall
	#28	Graph DBMS

Website

bitnine.net/agensgraph

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

www.snowflake.com

terminusdb.com

Technical documentation

bitnine.net/documentation

docs.heavy.ai

docs.snowflake.net/manuals/index.html

terminusdb.github.io/terminusdb/#

Developer

Bitnine Global Inc.

HEAVY.AI, Inc.

Snowflake Computing Inc.

DataChemist Ltd.

Initial release

2016

2014

2018

Current release

2.1, December 2018

5.10, January 2022

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

GPL V3

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

Prolog, Rust

Server operating systems

Linux
OS X
Windows

Linux

hosted

Linux

Data scheme

depending on used data model

yes

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

yes

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

SQL-like query language (WOQL)

APIs and other access methods

Cypher Query Language
JDBC

JDBC
ODBC
Thrift
Vega

CLI Client
JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C
Java
JavaScript
Python

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript (Node.js)
Python

JavaScript
Python

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Round robin

yes

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

yes

Journaling Streams

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 journaling

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

Role-based access control

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