DBMS > Cubrid vs. Hazelcast vs. Lovefield vs. Qdrant

System Properties Comparison Cubrid vs. Hazelcast vs. Lovefield vs. Qdrant

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

A widely adopted in-memory data grid

Embeddable relational database for web apps written in pure JavaScript

A high-performance vector database with neural network or semantic-based matching

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	0.97
Rank	#189	Overall
	#86	Relational DBMS

Score	5.72
Rank	#59	Overall
	#6	Key-value stores

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Website

cubrid.com (korean)
cubrid.org (english)

hazelcast.com

google.github.io/lovefield

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

cubrid.org/manuals

hazelcast.org/imdg/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

qdrant.tech/documentation

Developer

CUBRID Corporation, CUBRID Foundation

Hazelcast

Google

Qdrant

Initial release

2008

2014

2021

Current release

11.0, January 2021

5.3.6, November 2023

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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.

Implementation language

C, C++, Java

Java

JavaScript

Rust

Server operating systems

Linux
Windows

All OS with a Java VM

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

the object must implement a serialization strategy

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JCache
JPA
Memcached protocol
RESTful HTTP API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

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

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

JavaScript

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Event Listeners, Executor Services

Triggers

yes

Events

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Replicated Map

none

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control

Key-based authentication

More information provided by the system vendor

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

Recent citations in the news

CUBRID: A FOSS RDBMS to Realise Your Next Big Idea
26 April 2018, Open Source For You

NHN Willing to Be More Open
24 November 2008, 코리아타임스

provided by Google News

Event Stream Processing Market Exploring Future Growth 2023-2032 and Key Players - Cloudera, Inc., Hazelcast,
24 September 2024, EIN News

Hazelcast 5.4 real time data processing platform boosts AI and consistency
17 April 2024, VentureBeat

Hazelcast Expands Global Partner Program to Support Mission-Critical, AI Application Projects
20 August 2024, PR Newswire

Hazelcast Weaves Wider Logic Threads Through The Data Fabric
7 March 2024, Forbes

Hazelcast Showcases Real-Time Data Platform at 2024 Gartner Summit
15 May 2024, Datanami

provided by Google News

Qdrant review: A highly flexible option for vector search
29 July 2024, InfoWorld

Open source vector database startup Qdrant raises $28M
23 January 2024, TechCrunch

Vector database company Qdrant wants RAG to be more cost-effective
2 July 2024, VentureBeat

Qdrant Announces an Industry-First Hybrid Cloud Offering For Enterprise AI Applications
16 April 2024, Business Wire

Qdrant unveils hybrid vector algorithm for improved RAG
2 July 2024, Blocks & Files

provided by Google News

Share this page