DBMS > AgensGraph vs. GigaSpaces vs. HugeGraph vs. Snowflake vs. VelocityDB

System Properties Comparison AgensGraph vs. GigaSpaces vs. HugeGraph vs. Snowflake vs. VelocityDB

Editorial information provided by DB-Engines

Name

Description

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

A fast-speed and highly-scalable Graph DBMS

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

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Graph DBMS
Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Graph DBMS

Relational DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#16	Object oriented DBMS

Website

bitnine.net/agensgraph

www.gigaspaces.com

github.com/hugegraph
hugegraph.apache.org

www.snowflake.com

velocitydb.com

Technical documentation

bitnine.net/documentation

docs.gigaspaces.com/latest/landing.html

hugegraph.apache.org/docs

docs.snowflake.net/manuals/index.html

velocitydb.com/UserGuide

Developer

Bitnine Global Inc.

Gigaspaces Technologies

Baidu

Snowflake Computing Inc.

VelocityDB Inc

Initial release

2016

2000

2018

2014

2011

Current release

2.1, December 2018

15.5, September 2020

0.9

7.x

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache Version 2.0

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

Java, C++, .Net

Java

Server operating systems

Linux
OS X
Windows

Linux
macOS
Solaris
Windows

Linux
macOS
Unix

hosted

Any that supports .NET

Data scheme

depending on used data model

schema-free

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

SQL-99 for query and DML statements

yes

APIs and other access methods

Cypher Query Language
JDBC

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

Java API
RESTful HTTP API
TinkerPop Gremlin

CLI Client
JDBC
ODBC

.Net

Supported programming languages

C
Java
JavaScript
Python

.Net
C++
Java
Python
Scala

Groovy
Java
Python

JavaScript (Node.js)
Python

.Net

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

user defined functions

Triggers

yes, event driven architecture

similar concept for controling cloud resources

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

Role-based access control

Users, roles and permissions

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

Based on Windows Authentication

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