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

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

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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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

Primary database model

Graph DBMS
Relational DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.17
Rank	#320	Overall
	#29	Graph DBMS
	#143	Relational DBMS

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

bitnine.net/agensgraph

github.com/Softmotions/ejdb

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

www.snowflake.com

Technical documentation

bitnine.net/documentation

github.com/Softmotions/ejdb/blob/master/README.md

docs.heavy.ai

docs.snowflake.net/manuals/index.html

Developer

Bitnine Global Inc.

Softmotions

HEAVY.AI, Inc.

Snowflake Computing Inc.

Initial release

2016

2012

2016

2014

Current release

2.1, December 2018

5.10, January 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

GPLv2

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

Linux
OS X
Windows

server-less

Linux

hosted

Data scheme

depending on used data model

schema-free

yes

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

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

APIs and other access methods

Cypher Query Language
JDBC

in-process shared library

JDBC
ODBC
Thrift
Vega

CLI Client
JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

none

Sharding

Round robin

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source 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

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

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