DBMS > Couchbase vs. DuckDB vs. KeyDB vs. NuoDB vs. TigerGraph

System Properties Comparison Couchbase vs. DuckDB vs. KeyDB vs. NuoDB vs. TigerGraph

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

An embeddable, in-process, column-oriented SQL OLAP RDBMS

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

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

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

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

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

www.couchbase.com

duckdb.org

github.com/Snapchat/KeyDB
keydb.dev

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

www.tigergraph.com

Technical documentation

Developer

Couchbase, Inc.

EQ Alpha Technology Ltd.

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2011

2018

2019

2013

2017

Current release

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

1.0.0, June 2024

License

Commercial or Open Source

Open Source

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

Open Source

MIT License

Open Source

BSD-3

commercial

limited edition free

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.

Implementation language

C, C++, Go and Erlang

C++

Server operating systems

Linux
OS X
Windows

server-less

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

yes

SQL

Support of SQL

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

yes

SQL-like query language (GSQL)

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

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

ADO.NET
JDBC
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

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

C++
Java

Server-side scripts

Stored procedures

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

Lua

Java, SQL

yes

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

none

Multi-source replication
Source-replica replication

yes

Managed transparently by NuoDB

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
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

MVCC

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

In-memory capabilities

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

yes

Ephemeral buckets

yes

Temporary table

User concepts

Access control

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

simple password-based access control and ACL

Standard SQL roles/ privileges, Administrative Users

Role-based access control

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