DBMS > LMDB vs. Microsoft Azure AI Search vs. OrientDB vs. SQLite vs. Weaviate

System Properties Comparison LMDB vs. Microsoft Azure AI Search vs. OrientDB vs. SQLite vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

A high performant, light-weight, embedded key-value database library

Search-as-a-service for web and mobile app development

Multi-model DBMS (Document, Graph, Key/Value)

Widely used embeddable, in-process RDBMS

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

Primary database model

Key-value store

Search engine

Document store
Graph DBMS
Key-value store

Relational DBMS

Vector DBMS

Secondary database models

Vector DBMS

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

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	1.52
Rank	#153	Overall
	#5	Vector DBMS

Website

www.symas.com/symas-embedded-database-lmdb

azure.microsoft.com/en-us/services/search

orientdb.org

www.sqlite.org

github.com/weaviate/weaviate
weaviate.io

Technical documentation

www.lmdb.tech/doc

learn.microsoft.com/en-us/azure/search

www.orientdb.com/docs/last/index.html

www.sqlite.org/docs.html

weaviate.io/developers/weaviate

Developer

Symas

Microsoft

OrientDB LTD; CallidusCloud; SAP

Dwayne Richard Hipp

Weaviate B.V.

Initial release

2011

2015

2010

2000

2019

Current release

0.9.32, January 2024

3.2.29, March 2024

3.46.0 (23 May 2024), May 2024

1.19, May 2023

License

Commercial or Open Source

Open Source

commercial

Open Source

Apache version 2

Open Source

Public Domain

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

Java

Server operating systems

Linux
Unix
Windows

hosted

All OS with a Java JDK (>= JDK 6)

server-less

Data scheme

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

dynamic column types

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL-like query language, no joins

yes

SQL-92 is not fully supported

GraphQL is used as query language

APIs and other access methods

RESTful HTTP API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

C#
Java
JavaScript
Python

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Java, Javascript

Triggers

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

Multi-source replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

yes

using Azure authentication

Access rights for users and roles; record level security configurable

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,...
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Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

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

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.