DBMS > Apache Druid vs. DolphinDB vs. JaguarDB vs. Lovefield

System Properties Comparison Apache Druid vs. DolphinDB vs. JaguarDB vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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.

Performant, highly scalable DBMS for AI and IoT applications

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Relational DBMS
Time Series DBMS

Time Series DBMS
Vector DBMS

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Website

druid.apache.org

www.dolphindb.com

www.jaguardb.com

google.github.io/lovefield

Technical documentation

druid.apache.org/docs/latest/design

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

www.jaguardb.com/support.html

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Apache Software Foundation and contributors

DolphinDB, Inc

DataJaguar, Inc.

Google

Initial release

2012

2018

2015

2014

Current release

30.0.0, June 2024

v2.00.4, January 2022

3.3 July 2023

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache license v2

commercial

free community version available

Open Source

GPL V3.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

the server part. Clients available in other languages

JavaScript

Server operating systems

Linux
OS X
Unix

Linux
Windows

Linux

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

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

schema-less columns are supported

yes

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

SQL

Support of SQL

SQL for querying

SQL-like query language

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
RESTful HTTP/JSON API

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

JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

Multi-source replication

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Administrators, Users, Groups

rights management via user accounts

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