DBMS > Citus vs. LokiJS vs. OrientDB vs. Rockset vs. Snowflake

System Properties Comparison Citus vs. LokiJS vs. OrientDB vs. Rockset vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

In-memory JavaScript DBMS

Multi-model DBMS (Document, Graph, Key/Value)

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Document store

Document store
Graph DBMS
Key-value store

Document store

Relational DBMS

Secondary database models

Document store

Relational DBMS
Search engine

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

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.citusdata.com

github.com/techfort/LokiJS

orientdb.org

rockset.com

www.snowflake.com

Technical documentation

docs.citusdata.com

techfort.github.io/LokiJS

www.orientdb.com/docs/last/index.html

docs.rockset.com

docs.snowflake.net/manuals/index.html

Developer

OrientDB LTD; CallidusCloud; SAP

Rockset

Snowflake Computing Inc.

Initial release

2010

2014

2010

2019

2014

Current release

8.1, December 2018

3.2.29, March 2024

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

Apache version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

JavaScript

Java

C++

Server operating systems

Linux

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

All OS with a Java JDK (>= JDK 6)

hosted

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

dynamic typing

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

ingestion from XML files supported

yes

Secondary indexes

yes

via views

yes

all fields are automatically indexed

SQL

Support of SQL

yes

standard, with numerous extensions

SQL-like query language, no joins

Read-only SQL queries, including JOINs

yes

APIs and other access methods

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

JavaScript API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

HTTP REST

CLI Client
JDBC
ODBC

Supported programming languages

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

JavaScript

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

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

Java, Javascript

user defined functions

Triggers

yes

Hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Automatic sharding

yes

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

Access rights for users and organizations can be defined via Rockset console

Users with fine-grained authorization concept, user roles and pluggable 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.