DBMS > Apache Kylin vs. Brytlyt vs. EJDB vs. Faircom DB vs. Firebird

System Properties Comparison Apache Kylin vs. Brytlyt vs. EJDB vs. Faircom DB vs. Firebird

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

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

Firebird is an open source RDBMS forked from Borland's InterBase

Primary database model

Relational DBMS

Document store

Key-value store
Relational DBMS

Relational DBMS

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

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Website

kylin.apache.org

brytlyt.io

github.com/Softmotions/ejdb

www.faircom.com/products/faircom-db

www.firebirdsql.org

Technical documentation

kylin.apache.org/docs

docs.brytlyt.io

github.com/Softmotions/ejdb/blob/master/README.md

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

www.firebirdsql.org/en/reference-manuals

Developer

Apache Software Foundation, originally contributed from eBay Inc

Brytlyt

Softmotions

FairCom Corporation

Firebird Foundation

Initial release

2015

2016

2012

1979

2000

As fork of Borland's InterBase

Current release

3.1.0, July 2020

5.0, August 2023

V12, November 2020

5.0.0, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPLv2

commercial

Restricted, free version available

Open Source

Initial Developer's Public License

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++ and CUDA

ANSI C, C++

C and C++

Server operating systems

Linux

Linux
OS X
Windows

server-less

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

easily portable to other OSs

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Data scheme

yes

schema-free

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

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes, ANSI SQL Types, JSON, typed binary structures

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

yes, ANSI SQL with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

in-process shared library

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

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

.Net, JavaScript, C/C++

PSQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

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

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
Tunable consistency per server, database, table, and transaction

Foreign keys

Referential integrity

yes

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Features a multi-generational MVCC architecture, readers do not block writers

Durability

Support for making data persistent

yes

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

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

Users with fine-grained authorization concept

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