DBMS > AgensGraph vs. Drizzle vs. GBase vs. Qdrant vs. Snowflake

System Properties Comparison AgensGraph vs. Drizzle vs. GBase vs. Qdrant vs. Snowflake

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

A high-performance vector database with neural network or semantic-based matching

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

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Vector DBMS

Relational 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	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

bitnine.net/agensgraph

www.gbase.cn

github.com/qdrant/qdrant
qdrant.tech

www.snowflake.com

Technical documentation

bitnine.net/documentation

qdrant.tech/documentation

docs.snowflake.net/manuals/index.html

Developer

Bitnine Global Inc.

Drizzle project, originally started by Brian Aker

General Data Technology Co., Ltd.

Qdrant

Snowflake Computing Inc.

Initial release

2016

2008

2004

2021

2014

Current release

2.1, December 2018

7.2.4, September 2012

GBase 8a, GBase 8s, GBase 8c

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

GNU GPL

commercial

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

C++

C, Java, Python

Rust

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

Linux

Docker
Linux
macOS
Windows

hosted

Data scheme

depending on used data model

yes

schema-free

yes

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

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

with proprietary extensions

Standard with numerous extensions

yes

APIs and other access methods

Cypher Query Language
JDBC

JDBC

ADO.NET
C API
JDBC
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

CLI Client
JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

C
C++
Java
PHP

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

hooks for callbacks inside the server can be used.

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

yes

Collection-level replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable consistency

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

Key-based authentication

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

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