DBMS > EsgynDB vs. Infobright vs. Kingbase vs. Lovefield vs. Weaviate

System Properties Comparison EsgynDB vs. Infobright vs. Kingbase vs. Lovefield vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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

Embeddable relational database for web apps written in pure JavaScript

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

Primary database model

Relational DBMS

Vector DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

www.esgyn.cn

ignitetech.com/softwarelibrary/infobrightdb

www.kingbase.com.cn

google.github.io/lovefield

github.com/weaviate/weaviate
weaviate.io

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

weaviate.io/developers/weaviate

Developer

Esgyn

Ignite Technologies Inc.; formerly InfoBright Inc.

BeiJing KINGBASE Information technologies inc.

Google

Weaviate B.V.

Initial release

2015

2005

1999

2014

2019

Current release

V8.0, August 2021

2.1.12, February 2017

1.19, May 2023

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

Open Source

Apache 2.0

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++, Java

C and Java

JavaScript

Server operating systems

Linux

Linux
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

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

Knowledge Grid Technology used instead

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

SQL-like query language

via JavaScript builder pattern

GraphQL is used as query language

APIs and other access methods

ADO.NET
JDBC
ODBC

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

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

JavaScript

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

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.

Related products and services

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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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