DBMS > DolphinDB vs. Hawkular Metrics vs. JanusGraph vs. LokiJS vs. Oracle NoSQL

System Properties Comparison DolphinDB vs. Hawkular Metrics vs. JanusGraph vs. LokiJS vs. Oracle NoSQL

Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

In-memory JavaScript DBMS

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Time Series DBMS

Graph DBMS

Document store

Document store
Key-value store
Relational DBMS

Secondary database models

Relational DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Website

www.dolphindb.com

www.hawkular.org

janusgraph.org

github.com/techfort/LokiJS

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

docs.dolphindb.cn/en/help200/index.html

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.janusgraph.org

techfort.github.io/LokiJS

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

DolphinDB, Inc

Community supported by Red Hat

Linux Foundation; originally developed as Titan by Aurelius

Oracle

Initial release

2018

2014

2017

2014

2011

Current release

v2.00.4, January 2022

0.6.3, February 2023

24.1, May 2024

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

JavaScript

Java

Server operating systems

Linux
Windows

Linux
OS X
Windows

Linux
OS X
Unix
Windows

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

Linux
Solaris SPARC/x86

Data scheme

yes

schema-free

yes

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

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

via views

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

HTTP REST

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JavaScript API

RESTful HTTP API

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

Go
Java
Python
Ruby

Clojure
Java
Python

JavaScript

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

View functions in JavaScript

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on Cassandra

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

yes

none

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

none

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

yes

ACID

atomic operations within a single collection possible

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

off heap cache

User concepts

Access control

Administrators, Users, Groups

User authentification and security via Rexster Graph Server

Access rights for users and roles

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More resources

DB-Engines blog posts

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