DBMS > AgensGraph vs. GBase vs. Memgraph vs. Snowflake vs. Weaviate

System Properties Comparison AgensGraph vs. GBase vs. Memgraph vs. Snowflake vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

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

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

An open source graph database built for real-time streaming and compatible with Neo4j

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

An AI-native realtime vector database engine that integrates scalable machine learning models.

Primary database model

Graph 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	2.91
Rank	#94	Overall
	#7	Graph DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	1.48
Rank	#149	Overall
	#8	Vector DBMS

Website

bitnine.net/agensgraph

www.gbase.cn

memgraph.com

www.snowflake.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

bitnine.net/documentation

memgraph.com/docs

docs.snowflake.net/manuals/index.html

weaviate.io/developers/weaviate

Social network pages

Developer

Bitnine Global Inc.

General Data Technology Co., Ltd.

Memgraph Ltd

Snowflake Computing Inc.

Weaviate B.V.

Initial release

2016

2004

2017

2014

2019

Current release

2.1, December 2018

GBase 8a, GBase 8s, GBase 8c

1.19, May 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

BSL 1.1; commercial license for enterprise edition available

commercial

Open Source

commercial license available with Weaviate Enterprise

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, Java, Python

C and C++

Server operating systems

Linux
OS X
Windows

Linux

hosted

Data scheme

depending on used data model

yes

schema-free and schema-optional

yes

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

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

string, int, float, geo point, date, cross reference, fuzzy references

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

all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

SQL

Support of SQL

yes

Standard with numerous extensions

yes

GraphQL is used as query language

APIs and other access methods

Cypher Query Language
JDBC

ADO.NET
C API
JDBC
ODBC

Bolt protocol
Cypher query language

CLI Client
JDBC
ODBC

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

C
Java
JavaScript
Python

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

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

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

Sharding

dynamic graph partitioning

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication using RAFT

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

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

ACID

with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with periodic snapshot and write-ahead logging (WAL) of changes

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

yes

Users, roles and permissions

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

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Memgraph directly connects to your streaming infrastructure so you and your team...
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Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

Business Source License ensures a future for the Memgraph community MAGE algorithm...
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Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
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As a database supporting the development of generative AI and semantic search applications...
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Key customers

All companies that have data.
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Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
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Licensing and pricing models

You can check out our pricing model and licenses on the company website .
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Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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