DBMS > Apache Kylin vs. Dgraph vs. Faircom DB vs. KeyDB vs. LokiJS

System Properties Comparison Apache Kylin vs. Dgraph vs. Faircom DB vs. KeyDB vs. LokiJS

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

Distributed and scalable native Graph DBMS

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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

In-memory JavaScript DBMS

Primary database model

Relational DBMS

Graph DBMS

Key-value store
Relational DBMS

Key-value store

Document store

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

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

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	0.49
Rank	#260	Overall
	#42	Document stores

Website

kylin.apache.org

dgraph.io

www.faircom.com/products/faircom-db

github.com/Snapchat/KeyDB
keydb.dev

github.com/techfort/LokiJS

Technical documentation

kylin.apache.org/docs

dgraph.io/docs

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

docs.keydb.dev

techfort.github.io/LokiJS

Developer

Apache Software Foundation, originally contributed from eBay Inc

Dgraph Labs, Inc.

FairCom Corporation

EQ Alpha Technology Ltd.

Initial release

2015

2016

1979

2019

2014

Current release

3.1.0, July 2020

V12, November 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Restricted, free version available

Open Source

BSD-3

Open Source

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

ANSI C, C++

C++

JavaScript

Server operating systems

Linux

Linux
OS X
Windows

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

easily portable to other OSs

Linux

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

schema-free

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

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

yes

via views

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes, ANSI SQL with proprietary extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

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

Proprietary protocol

RESP - REdis Serialization Protoco

JavaScript API

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

JavaScript

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Lua

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

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

Multi-source replication
Source-replica replication

none

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

Eventual Consistency
Strong eventual consistency with CRDTs

none

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

Optimistic locking, atomic execution of commands blocks and scripts

atomic operations within a single collection possible

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

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

In-memory capabilities

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

yes

User concepts

Access control

Planned for future releases

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

simple password-based access control and ACL

More information provided by the system vendor

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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