DBMS > DolphinDB vs. Graphite vs. Hawkular Metrics vs. LokiJS vs. Microsoft Azure Cosmos DB

System Properties Comparison DolphinDB vs. Graphite vs. Hawkular Metrics vs. LokiJS vs. Microsoft Azure Cosmos DB

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.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

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

In-memory JavaScript DBMS

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Time Series DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

www.dolphindb.com

github.com/graphite-project/graphite-web

www.hawkular.org

github.com/techfort/LokiJS

azure.microsoft.com/services/cosmos-db

Technical documentation

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

graphite.readthedocs.io

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

techfort.github.io/LokiJS

learn.microsoft.com/azure/cosmos-db

Developer

DolphinDB, Inc

Chris Davis

Community supported by Red Hat

Microsoft

Initial release

2018

2006

2014

Current release

v2.00.4, January 2022

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

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

C++

Python

Java

JavaScript

Server operating systems

Linux
Windows

Linux
Unix

Linux
OS X
Windows

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

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

yes

JSON types

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

All properties auto-indexed by default

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 API
Sockets

HTTP REST

JavaScript API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

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

JavaScript (Node.js)
Python

Go
Java
Python
Ruby

JavaScript

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

yes

View functions in JavaScript

JavaScript

Triggers

yes

via Hawkular Alerting

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

based on Cassandra

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

based on Cassandra

none

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

none

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

atomic operations within a single collection possible

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

locking

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 rights can be defined down to the item level

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