DBMS > AnzoGraph DB vs. Milvus vs. MySQL vs. TerarkDB

System Properties Comparison AnzoGraph DB vs. Milvus vs. MySQL vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

A DBMS designed for efficient storage of vector data and vector similarity searches

Widely used open source RDBMS

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Graph DBMS
RDF store

Vector DBMS

Relational DBMS

Key/Value like access via memcached API

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	0.22
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	3.01
Rank	#89	Overall
	#4	Vector DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

cambridgesemantics.com/anzograph

milvus.io

www.mysql.com

github.com/bytedance/terarkdb

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

milvus.io/docs/overview.md

dev.mysql.com/doc

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Cambridge Semantics

Oracle

since 2010, originally MySQL AB, then Sun

ByteDance, originally Terark

Initial release

2018

2019

1995

2016

Current release

2.3, January 2021

2.4.4, May 2024

9.0.0, July 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

restricted open source version available

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.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

C++, Go

C and C++

C++

Server operating systems

Linux

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

Typing

predefined data types such as float or date

Vector, Numeric and String

yes

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

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

with proprietary extensions

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

C++ API
Java API

Supported programming languages

C++
Java
Python

C++
Go
Java
JavaScript (Node.js)
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++
Java

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Access rights for users and roles

Role based access control and fine grained access rights

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready...
» more

Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
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Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more

Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more

Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
» more

Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
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