DBMS > Apache IoTDB vs. HyperSQL vs. Milvus vs. MonetDB vs. OpenEdge

System Properties Comparison Apache IoTDB vs. HyperSQL vs. Milvus vs. MonetDB vs. OpenEdge

Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

A relational database management system that stores data in columns

Application development environment with integrated database management system

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	3.14
Rank	#85	Overall
	#46	Relational DBMS

Score	3.01
Rank	#89	Overall
	#4	Vector DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	3.69
Rank	#78	Overall
	#42	Relational DBMS

Website

www.progress.com/openedge

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

hsqldb.org/web/hsqlDocsFrame.html

milvus.io/docs/overview.md

www.monetdb.org/Documentation

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Apache Software Foundation

MonetDB BV

Progress Software Corporation

Initial release

2018

2001

2019

2004

1984

Current release

1.1.0, April 2023

2.7.2, June 2023

2.4.4, May 2024

Dec2023 (11.49), December 2023

OpenEdge 12.2, March 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

based on BSD license

Open Source

Apache Version 2.0

Open Source

Mozilla Public License 2.0

commercial

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

Java

C++, Go

Server operating systems

All OS with a Java VM (>= 1.8)

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL 2003 with some extensions

yes

close to SQL 92

APIs and other access methods

JDBC
Native API

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

All languages supporting JDBC/ODBC
Java

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

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

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

yes

Java, SQL

yes, in SQL, C, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

none

Sharding

Sharding via remote tables

horizontal partitioning

since Version 11.4

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

none

Source-replica replication available in experimental status

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate 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

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

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

Users and groups

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.

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