DBMS > Apache Kylin vs. Couchbase vs. etcd vs. HBase vs. Percona Server for MongoDB

System Properties Comparison Apache Kylin vs. Couchbase vs. etcd vs. HBase vs. Percona Server for MongoDB

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

A distributed reliable key-value store

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

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

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	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	0.60
Rank	#246	Overall
	#39	Document stores

Website

kylin.apache.org

www.couchbase.com

etcd.io
github.com/etcd-io/etcd

hbase.apache.org

www.percona.com/mongodb/software/percona-server-for-mongodb

Technical documentation

kylin.apache.org/docs

docs.couchbase.com

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

hbase.apache.org/book.html

docs.percona.com/percona-distribution-for-mongodb

Developer

Apache Software Foundation, originally contributed from eBay Inc

Couchbase, Inc.

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Percona

Initial release

2015

2011

2008

2015

Current release

3.1.0, July 2020

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

3.4, August 2019

2.3.4, January 2021

3.4.10-2.10, November 2017

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

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

Open Source

Apache Version 2.0

Open Source

Apache version 2

Open Source

GPL Version 2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C, C++, Go and Erlang

Java

C++

Server operating systems

Linux

Linux
OS X
Windows

FreeBSD
Linux
Windows

experimental

Linux
Unix
Windows

using Cygwin

Linux

Data scheme

yes

schema-free

schema-free, schema definition possible

schema-free

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

ANSI SQL for queries (using Apache Calcite)

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

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

gRPC
JSON over HTTP

Java API
RESTful HTTP API
Thrift

proprietary protocol using JSON

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C
C#
C++
Groovy
Java
PHP
Python
Scala

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Server-side scripts

Stored procedures

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

yes

Coprocessors in Java

JavaScript

Triggers

yes

via the TAP protocol

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Multi-source replication
Source-replica replication

Source-replica replication

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

Immediate Consistency

Immediate Consistency or Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

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

via In-Memory Engine

User concepts

Access control

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

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

Access rights for users and roles

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