DBMS > Couchbase vs. DataFS vs. Dgraph vs. Microsoft Azure Synapse Analytics

System Properties Comparison Couchbase vs. DataFS vs. Dgraph vs. Microsoft Azure Synapse Analytics

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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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Distributed and scalable native Graph DBMS

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

Graph DBMS

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

Score	16.74
Rank	#33	Overall
	#5	Document stores

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	1.39
Rank	#155	Overall
	#15	Graph DBMS

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Website

www.couchbase.com

newdatabase.com

dgraph.io

azure.microsoft.com/services/synapse-analytics

Technical documentation

docs.couchbase.com

dev.mobiland.com/Overview.xsp

dgraph.io/docs

docs.microsoft.com/azure/synapse-analytics

Developer

Couchbase, Inc.

Mobiland AG

Dgraph Labs, Inc.

Microsoft

Initial release

2011

2018

2016

Current release

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

1.1.263, October 2022

License

Commercial or Open Source

Open Source

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

commercial

Open Source

Apache 2.0

commercial

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

Windows

Linux
OS X
Windows

hosted

Data scheme

schema-free

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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.

Secondary indexes

yes

SQL

Support of SQL

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

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

.NET Client API
Proprietary client DLL
WinRT client

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
C
C#
C++
VB.Net

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

C#
Java
PHP

Server-side scripts

Stored procedures

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

Transact SQL

Triggers

yes

via the TAP protocol

no, except callback-events from server when changes happened

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Proprietary Sharding system

yes

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Synchronous replication via Raft

yes

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

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

User concepts

Access control

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

Windows-Profile

Planned for future releases

yes

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