DBMS > HugeGraph vs. Snowflake vs. SQream DB

System Properties Comparison HugeGraph vs. Snowflake vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Graph DBMS

Relational DBMS

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

www.snowflake.com

sqream.com

Technical documentation

hugegraph.apache.org/docs

docs.snowflake.net/manuals/index.html

docs.sqream.com

Developer

Baidu

Snowflake Computing Inc.

SQream Technologies

Initial release

2018

2014

2017

Current release

0.9

2022.1.6, December 2022

License

Commercial or Open Source

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

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Implementation language

Java

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux
macOS
Unix

hosted

Linux

Data scheme

yes

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

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

also supports composite index and range index

SQL

Support of SQL

yes

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

CLI Client
JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

Groovy
Java
Python

JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

user defined functions

user defined functions in Python

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

yes

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

yes

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

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

Users, roles and permissions

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

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