DBMS > Kingbase vs. NebulaGraph vs. Weaviate

System Properties Comparison Kingbase vs. NebulaGraph vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

A distributed, linear scalable, high perfomant Graph DBMS

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

Primary database model

Relational DBMS

Graph DBMS

Vector DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.41
Rank	#260	Overall
	#120	Relational DBMS

Score	1.61
Rank	#136	Overall
	#11	Graph DBMS

Score	1.86
Rank	#123	Overall
	#11	Vector DBMS

Website

www.kingbase.com.cn

github.com/vesoft-inc/nebula
www.nebula-graph.io

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.nebula-graph.io

weaviate.io/developers/weaviate

Developer

BeiJing KINGBASE Information technologies inc.

Vesoft Inc.

Weaviate B.V.

Initial release

1999

2019

Current release

V8.0, August 2021

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0 + Common Clause 1.0

Open Source

commercial license available with Weaviate Enterprise

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and Java

C++

Server operating systems

Linux
Windows

Linux

Data scheme

yes

Strong typed schema

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

Nebula Graph internally uses the Key-Value store RocksDB for persistency. The vertices, edges, and their properties are stored as Key while their values are stored as Value. The primary indexes are per Key and secondary indexes are per Value.

yes

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

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language

GraphQL is used as query language

APIs and other access methods

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

Browser interface
console (shell)
Cypher Query Language
GO Object Graph Mapper
Java Object Graph Mapper
NGBatis

ORM framework for NebulaGraph and Spring-Boot
Proprietary native API
Python Object Graph Mapper
Query language nGQL

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

.Net
C++
Go
Java
PHP
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Causal Clustering using Raft protocol

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

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

using RocksDB

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

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more

Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
» more

Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
» more

Key customers

All companies that have data.
» more

Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more

Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Weaviate, an ANN Database with CRUD support
2 February 2021, Etienne Dilocker, SeMI Technologies (sponsor)

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