DBMS > Couchbase vs. EsgynDB vs. Microsoft Azure SQL Database vs. NuoDB vs. Spark SQL

System Properties Comparison Couchbase vs. EsgynDB vs. Microsoft Azure SQL Database vs. NuoDB vs. Spark SQL

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Database as a Service offering with high compatibility to Microsoft SQL Server

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Document store

Relational 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

Document store
Graph DBMS
Spatial DBMS

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

www.couchbase.com

www.esgyn.cn

azure.microsoft.com/en-us/products/azure-sql/database

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

spark.apache.org/sql

Technical documentation

docs.couchbase.com

docs.microsoft.com/en-us/azure/azure-sql

doc.nuodb.com

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Couchbase, Inc.

Esgyn

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

Apache Software Foundation

Initial release

2011

2015

2010

2013

2014

Current release

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

V12

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

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

commercial

limited edition free

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

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++, Java

C++

Scala

Server operating systems

Linux
OS X
Windows

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

yes

SQL-like DML and DDL statements

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

ADO.NET
JDBC
ODBC

JDBC
ODBC

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/ADO.Net

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

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

Java
Python
R
Scala

Server-side scripts

Stored procedures

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

Java Stored Procedures

Transact SQL

Java, SQL

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

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

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication between multi datacenters

yes, with always 3 replicas available

yes

Managed transparently by NuoDB

none

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

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

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.

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

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