DBMS > Alibaba Cloud AnalyticDB for MySQL vs. JanusGraph vs. Weaviate

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. JanusGraph vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

A real-time data warehousing service that can process petabytes of data with high concurrency and low latency. It is fully compatible with the MySQL protocol.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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

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

Score	0.84
Rank	#205	Overall
	#95	Relational DBMS

Score	1.78
Rank	#127	Overall
	#10	Graph DBMS

Score	1.95
Rank	#115	Overall
	#10	Vector DBMS

Website

www.alibabacloud.com/product/analyticdb-for-mysql

janusgraph.org

github.com/weaviate/weaviate
weaviate.io

Technical documentation

www.alibabacloud.com/help/doc-detail/93776.htm

docs.janusgraph.org

weaviate.io/developers/weaviate

Developer

Alibaba

Linux Foundation; originally developed as Titan by Aurelius

Weaviate B.V.

Initial release

2017

2019

Current release

1.0.0, October 2023

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

hosted

Linux
OS X
Unix
Windows

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

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

SQL

Support of SQL

yes

GraphQL is used as query language

APIs and other access methods

JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

C#
Java
PHP
Python

Clojure
Java
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

API Keys
OpenID Connect Discovery

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More resources

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