DBMS > Couchbase vs. Microsoft Azure SQL Database vs. SAP HANA vs. Stardog vs. TigerGraph

System Properties Comparison Couchbase vs. Microsoft Azure SQL Database vs. SAP HANA vs. Stardog 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

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

In-memory, column based data store. Available as appliance or cloud service

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

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

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

www.couchbase.com

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

www.sap.com/products/hana.html

www.stardog.com

www.tigergraph.com

Technical documentation

docs.couchbase.com

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

help.sap.com/hana

docs.stardog.com

docs.tigergraph.com

Developer

Couchbase, Inc.

Microsoft

SAP

Stardog-Union

Initial release

2011

2010

2017

Current release

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

V12

2.0 SPS07 (April 4, 2023), April 2023

7.3.0, May 2020

License

Commercial or Open Source

Open Source

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

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based 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++

Java

C++

Server operating systems

Linux
OS X
Windows

hosted

Appliance or cloud-service

Linux
macOS
Windows

Linux

Data scheme

schema-free

yes

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

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

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

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

ADO.NET
JDBC
ODBC

JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

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

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

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

Transact SQL

SQLScript, R

user defined functions and aggregates, HTTP Server extensions in Java

yes

Triggers

yes

via the TAP protocol

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

yes, with always 3 replicas available

yes

Multi-source replication in HA-Cluster

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

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Relationships in graphs

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

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

yes

Access rights for users and roles

Role-based access control

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