DBMS > Couchbase vs. HEAVY.AI vs. Lovefield vs. NuoDB vs. Qdrant

System Properties Comparison Couchbase vs. HEAVY.AI vs. Lovefield vs. NuoDB vs. Qdrant

Editorial information provided by DB-Engines

Name

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable relational database for web apps written in pure JavaScript

NuoDB is a webscale distributed database that supports SQL and ACID transactions

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

Primary database model

Document store

Relational DBMS

Vector DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Spatial DBMS

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Score	1.28
Rank	#167	Overall
	#7	Vector DBMS

Website

www.couchbase.com

github.com/heavyai/heavydb
www.heavy.ai

google.github.io/lovefield

www.3ds.com/nuodb-distributed-sql-database

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

docs.couchbase.com

docs.heavy.ai

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

doc.nuodb.com

qdrant.tech/documentation

Developer

Couchbase, Inc.

HEAVY.AI, Inc.

Google

Dassault Systèmes

originally NuoDB, Inc.

Qdrant

Initial release

2011

2016

2014

2013

2021

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

5.10, January 2022

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

commercial

limited edition free

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++, Go and Erlang

C++ and CUDA

JavaScript

C++

Rust

Server operating systems

Linux
OS X
Windows

Linux

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

tested with Chrome, Firefox, IE, Safari

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Docker
Linux
macOS
Windows

Data scheme

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.

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

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

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

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

Java, SQL

Triggers

yes

via the TAP protocol

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

Round robin

none

data is dynamically stored/cached on the nodes where it is read/written

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication

none

yes

Managed transparently by NuoDB

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Ephemeral buckets

yes

using MemoryDB

yes

Temporary table

yes

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

Key-based authentication

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