DBMS > Graph Engine vs. Hive vs. Milvus vs. OushuDB vs. TDSQL for MySQL

System Properties Comparison Graph Engine vs. Hive vs. Milvus vs. OushuDB vs. TDSQL for MySQL

Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Graph DBMS
Key-value store

Relational DBMS

Vector DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Score	0.85
Rank	#205	Overall
	#95	Relational DBMS

Website

www.graphengine.io

hive.apache.org

milvus.io

www.oushu.com/product/oushuDB

www.tencentcloud.com/products/dcdb

Technical documentation

www.graphengine.io/docs/manual

cwiki.apache.org/confluence/display/Hive/Home

milvus.io/docs/overview.md

www.oushu.com/documentation

www.tencentcloud.com/document/product/1042

Developer

Microsoft

Apache Software Foundation

initially developed by Facebook

Oushu

Tencent

Initial release

2010

2012

2019

2013

Current release

3.1.3, April 2022

2.3.4, January 2024

4.0.1, August 2020

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

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.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

.NET and C

Java

C++, Go

Server operating systems

.NET

All OS with a Java VM

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux

hosted

Data scheme

yes

Typing

predefined data types such as float or date

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

Full-featured ANSI SQL support

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Thrift

RESTful HTTP API

JDBC
ODBC

Supported programming languages

C#
C++
F#
Visual Basic

C++
Java
PHP
Python

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

C
C++

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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, groups and roles

Role based access control and fine grained access rights

Kerberos, SSL and role based access

Users with fine-grained authorization concept

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...
» more

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...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

Trinity
2 June 2023, microsoft.com

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

The graph analytics landscape 2019 - DataScienceCentral.com
27 February 2019, Data Science Central

provided by Google News

Apache Software Foundation Announces Apache® Hive 4.0
30 April 2024, GlobeNewswire

ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0
2 May 2024, Datanami

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

DataCentral: Uber's Observability and Chargeback Platform
1 February 2024, Uber

provided by Google News

How NVIDIA GPU Acceleration Supercharged Milvus Vector Database
26 March 2024, The New Stack

AI-Powered Search Engine With Milvus Vector Database on Vultr
31 January 2024, SitePoint

Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search
20 March 2024, GlobeNewswire

Zilliz Unveils Game-Changing Features for Vector Search
22 March 2024, Datanami

IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI
9 April 2024, IBM

provided by Google News

China's answer to Snowflake is shaping as data demands upgrade
8 September 2021, PingWest

provided by Google News

Tencent Cloud Database recognised for cloud database management systems
21 December 2022, IT Brief Australia

Tencent Cloud Distributed Database Ranks First in the Growth Index: Frost & Sullivan's "2021 China Distributed ...
16 May 2022, PR Newswire Asia

Indonesia's Allo Bank taps Tencent Cloud to enhance digital banking services
6 July 2023, FinTech Futures

Tencent Cloud and Allo Bank partner to enhance digital banking in Indonesia, ETCIO SEA
6 July 2023, ETCIO South East Asia

Chinese government blocks use of Intel, AMD chips in hardware
25 March 2024, Yahoo Singapore News

provided by Google News

Share this page