DBMS > Altibase vs. Apache Kylin vs. Couchbase vs. EventStoreDB vs. Faircom DB

System Properties Comparison Altibase vs. Apache Kylin vs. Couchbase vs. EventStoreDB vs. Faircom DB

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

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

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Primary database model

Relational DBMS

Document store

Event Store

Key-value store
Relational DBMS

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	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Website

www.faircom.com/products/faircom-db

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

kylin.apache.org/docs

docs.couchbase.com

developers.eventstore.com

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

Developer

Altibase

Apache Software Foundation, originally contributed from eBay Inc

Couchbase, Inc.

Event Store Limited

FairCom Corporation

Initial release

1999

2015

2011

2012

1979

Current release

v7.3, 2023, August 2023

3.1.0, July 2020

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

21.2, February 2021

V12, November 2020

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache Version 2.0

Open Source

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

Open Source

commercial

Restricted, free version available

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

C++

Java

C, C++, Go and Erlang

ANSI C, C++

Server operating systems

AIX
HP-UX
Linux

Linux

Linux
OS X
Windows

Linux
Windows

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Data scheme

yes

schema-free

schema free, schema optional, schema required, partial schema,

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

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-92

ANSI SQL for queries (using Apache Calcite)

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

yes, ANSI SQL with proprietary extensions

APIs and other access methods

JDBC
ODBC
Proprietary protocol

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
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

Supported programming languages

C
C++
Java

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

Server-side scripts

Stored procedures

stored procedures and stored functions

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

yes

.Net, JavaScript, C/C++

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

including cross data center replication
Source-replica replication

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

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
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

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

fine grained access rights according to SQL-standard

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

Fine grained access rights according to SQL-standard with additional protections for files

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