DBMS > DolphinDB vs. Hawkular Metrics vs. HBase vs. LokiJS vs. Newts

System Properties Comparison DolphinDB vs. Hawkular Metrics vs. HBase vs. LokiJS vs. Newts

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.

Wide-column store based on Apache Hadoop and on concepts of BigTable

In-memory JavaScript DBMS

Time Series DBMS based on Cassandra

Primary database model

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	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

www.dolphindb.com

www.hawkular.org

hbase.apache.org

github.com/techfort/LokiJS

opennms.github.io/newts

Technical documentation

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

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

hbase.apache.org/book.html

techfort.github.io/LokiJS

github.com/OpenNMS/newts/wiki

Developer

DolphinDB, Inc

Community supported by Red Hat

Apache Software Foundation

Apache top-level project, originally developed by Powerset

OpenNMS Group

Initial release

2018

2014

2008

2014

Current release

v2.00.4, January 2022

2.3.4, January 2021

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache 2.0

Open Source

Apache version 2

Open Source

Apache 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

C++

Java

JavaScript

Java

Server operating systems

Linux
Windows

Linux
OS X
Windows

Linux
Unix
Windows

using Cygwin

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

Linux
OS X
Windows

Data scheme

yes

schema-free

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

HTTP REST

Java API
RESTful HTTP API
Thrift

JavaScript API

HTTP REST
Java API

Supported programming languages

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

Go
Java
Python
Ruby

C
C#
C++
Groovy
Java
PHP
Python
Scala

JavaScript

Java

Server-side scripts

Stored procedures

yes

Coprocessors in Java

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

Sharding

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

none

selectable replication factor

based on Cassandra

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 or Eventual Consistency

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

Transaction concepts

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

yes

Single row ACID (across millions of columns)

atomic operations within a single collection possible

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

Administrators, Users, Groups

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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