DBMS > Apache Kylin vs. Citus vs. LokiJS vs. Oracle vs. Qdrant

System Properties Comparison Apache Kylin vs. Citus vs. LokiJS vs. Oracle vs. Qdrant

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 hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

In-memory JavaScript DBMS

Widely used RDBMS

A high-performance vector database with neural network or semantic-based matching

Primary database model

Secondary database models

Document store

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Website

kylin.apache.org

www.citusdata.com

github.com/techfort/LokiJS

www.oracle.com/database

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

kylin.apache.org/docs

docs.citusdata.com

techfort.github.io/LokiJS

docs.oracle.com/en/database

qdrant.tech/documentation

Developer

Apache Software Foundation, originally contributed from eBay Inc

Oracle

Qdrant

Initial release

2015

2010

2014

1980

2021

Current release

3.1.0, July 2020

8.1, December 2018

23c, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

AGPL, commercial license also available

Open Source

commercial

restricted free version is available

Open Source

Apache Version 2.0

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

JavaScript

C and C++

Rust

Server operating systems

Linux

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

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

yes

Secondary indexes

yes

via views

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

standard, with numerous extensions

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

JavaScript API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

View functions in JavaScript

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

none

Multi-source replication
Source-replica replication

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Key-based authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.