DBMS > Couchbase vs. Firebase Realtime Database vs. Microsoft SQL Server vs. RavenDB vs. TerarkDB

System Properties Comparison Couchbase vs. Firebase Realtime Database vs. Microsoft SQL Server vs. RavenDB vs. TerarkDB

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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Microsofts flagship relational DBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

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

Document store
Graph DBMS
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.couchbase.com

firebase.google.com/products/realtime-database

www.microsoft.com/en-us/sql-server

ravendb.net

github.com/bytedance/terarkdb

Technical documentation

docs.couchbase.com

firebase.google.com/docs/database

learn.microsoft.com/en-US/sql/sql-server

ravendb.net/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Couchbase, Inc.

Google

acquired by Google 2014

Microsoft

Hibernating Rhinos

ByteDance, originally Terark

Initial release

2011

2012

1989

2010

2016

Current release

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

SQL Server 2022, November 2022

5.4, July 2022

License

Commercial or Open Source

Open Source

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

commercial

restricted free version is available

Open Source

AGPL version 3, commercial license available

commercial

restricted open source version available

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++

Server operating systems

Linux
OS X
Windows

hosted

Linux
Windows

Linux
macOS
Raspberry Pi
Windows

Data scheme

schema-free

yes

schema-free

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 query language (RQL)

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

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

C++ API
Java API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java
JavaScript
Objective-C

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

C++
Java

Server-side scripts

Stored procedures

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

limited functionality with using 'rules'

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

via the TAP protocol

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

yes, but depending on the SQL-Server Edition

Multi-source replication

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

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

ACID, Cluster-wide transaction available

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

Ephemeral buckets

yes

User concepts

Access control

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

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

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