DBMS > AgensGraph vs. LeanXcale vs. Machbase Neo vs. Netezza vs. Weaviate

System Properties Comparison AgensGraph vs. LeanXcale vs. Machbase Neo vs. Netezza vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

TimeSeries DBMS for AIoT and BigData

Data warehouse and analytics appliance part of IBM PureSystems

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

Primary database model

Graph DBMS
Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Vector DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

bitnine.net/agensgraph

www.leanxcale.com

machbase.com

www.ibm.com/products/netezza

github.com/weaviate/weaviate
weaviate.io

Technical documentation

bitnine.net/documentation

machbase.com/dbms

weaviate.io/developers/weaviate

Developer

Bitnine Global Inc.

LeanXcale

Machbase

IBM

Weaviate B.V.

Initial release

2016

2015

2013

2000

2019

Current release

2.1, December 2018

V8.0, August 2023

1.19, May 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free test version available

commercial

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

Server operating systems

Linux
OS X
Windows

Linux
macOS
Windows

Linux

included in appliance

Data scheme

depending on used data model

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.

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

through Apache Derby

SQL-like query language

yes

GraphQL is used as query language

APIs and other access methods

Cypher Query Language
JDBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

JDBC
ODBC
OLE DB

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

C
Java
JavaScript
Python

C
Java
Scala

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

Source-replica replication

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

In-memory capabilities

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

yes

volatile and lookup table

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

Users with fine-grained authorization concept

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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