DBMS > Apache Kylin vs. Couchbase vs. Microsoft Access vs. Riak TS

System Properties Comparison Apache Kylin vs. Couchbase vs. Microsoft Access vs. Riak TS

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Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

kylin.apache.org

www.couchbase.com

www.microsoft.com/en-us/microsoft-365/access

Technical documentation

kylin.apache.org/docs

docs.couchbase.com

developer.microsoft.com/en-us/access

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Apache Software Foundation, originally contributed from eBay Inc

Couchbase, Inc.

Microsoft

Open Source, formerly Basho Technologies

Initial release

2015

2011

1992

2015

Current release

3.1.0, July 2020

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

1902 (16.0.11328.20222), March 2019

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

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

commercial

Bundled with Microsoft Office

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++, Go and Erlang

C++

Erlang

Server operating systems

Linux

Linux
OS X
Windows

Windows

Not a real database server, but making use of DLLs

Linux
OS X

Data scheme

yes

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.

Secondary indexes

yes

restricted

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

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

yes

but not compliant to any SQL standard

yes, limited

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

ADO.NET
DAO
ODBC
OLE DB

HTTP API
Native Erlang Interface

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

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

yes

since Access 2010 using the ACE-engine

Erlang

Triggers

yes

via the TAP protocol

yes

since Access 2010 using the ACE-engine

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

ACID

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

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.

a simple user-level security was built in till version Access 2003

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