DBMS > Graph Engine vs. Hypertable vs. Milvus vs. MonetDB vs. STSdb

System Properties Comparison Graph Engine vs. Hypertable vs. Milvus vs. MonetDB vs. STSdb

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

An open source BigTable implementation based on distributed file systems such as Hadoop

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

A relational database management system that stores data in columns

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Graph DBMS
Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	2.78
Rank	#103	Overall
	#3	Vector DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

www.graphengine.io

milvus.io

www.monetdb.org

github.com/STSSoft/STSdb4

Technical documentation

www.graphengine.io/docs/manual

milvus.io/docs/overview.md

www.monetdb.org/Documentation

Developer

Microsoft

Hypertable Inc.

MonetDB BV

STS Soft SC

Initial release

2010

2009

2019

2004

2011

Current release

0.9.8.11, March 2016

2.3.4, January 2024

Dec2023 (11.49), December 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

MIT License

Open Source

GNU version 3. Commercial license available

Open Source

Apache Version 2.0

Open Source

Mozilla Public License 2.0

Open Source

GPLv2, commercial license 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

.NET and C

C++

C++, Go

Server operating systems

.NET

Linux
OS X
Windows

an inofficial Windows port is available

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

FreeBSD
Linux
OS X
Solaris
Windows

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes

primitive types and user defined types (classes)

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

APIs and other access methods

RESTful HTTP API

C++ API
Thrift

RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

.NET Client API

Supported programming languages

C#
C++
F#
Visual Basic

C++
Java
Perl
PHP
Python
Ruby

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

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C#
Java

Server-side scripts

Stored procedures

yes

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Sharding via remote tables

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

none

Source-replica replication available in experimental status

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable 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

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

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

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

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