DBMS > DolphinDB vs. Fauna vs. Hawkular Metrics vs. LevelDB vs. LokiJS

System Properties Comparison DolphinDB vs. Fauna vs. Hawkular Metrics vs. LevelDB vs. LokiJS

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.

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

In-memory JavaScript DBMS

Primary database model

Time Series DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Time Series DBMS

Key-value store

Document store

Secondary database models

Relational DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.43
Rank	#264	Overall
	#42	Document stores

Website

www.dolphindb.com

fauna.com

www.hawkular.org

github.com/google/leveldb

github.com/techfort/LokiJS

Technical documentation

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

docs.fauna.com

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

github.com/google/leveldb/blob/main/doc/index.md

techfort.github.io/LokiJS

Developer

DolphinDB, Inc

Fauna, Inc.

Community supported by Red Hat

Google

Initial release

2018

2014

2011

2014

Current release

v2.00.4, January 2022

1.23, February 2021

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Apache 2.0

Open Source

BSD

Open Source

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

C++

Scala

Java

C++

JavaScript

Server operating systems

Linux
Windows

hosted

Linux
OS X
Windows

Illumos
Linux
OS X
Windows

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

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

via views

SQL

Support of SQL

SQL-like query language

APIs and other access methods

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

RESTful HTTP API

HTTP REST

JavaScript API

Supported programming languages

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

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

Go
Java
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions

View functions in JavaScript

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

selectable replication factor

based on Cassandra

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

atomic operations within a single collection possible

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

Administrators, Users, Groups

Identity management, authentication, and access control

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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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