DBMS > Couchbase vs. EXASOL vs. HBase vs. Microsoft Azure Synapse Analytics vs. RDF4J

System Properties Comparison Couchbase vs. EXASOL vs. HBase vs. Microsoft Azure Synapse Analytics vs. RDF4J

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

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	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

www.couchbase.com

www.exasol.com

hbase.apache.org

azure.microsoft.com/services/synapse-analytics

rdf4j.org

Technical documentation

docs.couchbase.com

www.exasol.com/resources

hbase.apache.org/book.html

docs.microsoft.com/azure/synapse-analytics

rdf4j.org/documentation

Developer

Couchbase, Inc.

Exasol

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2011

2000

2008

2016

2004

Current release

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

2.3.4, January 2021

License

Commercial or Open Source

Open Source

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

commercial

Open Source

Apache version 2

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Java

C++

Java

Server operating systems

Linux
OS X
Windows

Linux
Unix
Windows

using Cygwin

hosted

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

schema-free, schema definition possible

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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
JDBC
ODBC
WebSocket

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java
Lua
Python
R

C
C#
C++
Groovy
Java
PHP
Python
Scala

C#
Java
PHP

Java
PHP
Python

Server-side scripts

Stored procedures

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

user defined functions

yes

Coprocessors in Java

Transact SQL

yes

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication
Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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 or Eventual Consistency

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

Single row ACID (across millions of columns)

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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.

Access rights for users, groups and roles according to SQL-standard

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

yes

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