DBMS > DolphinDB vs. Graph Engine vs. Lovefield vs. SwayDB

System Properties Comparison DolphinDB vs. Graph Engine vs. Lovefield vs. SwayDB

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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.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Embeddable relational database for web apps written in pure JavaScript

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Time Series DBMS

Graph DBMS
Key-value store

Relational DBMS

Key-value 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	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

www.dolphindb.com

www.graphengine.io

google.github.io/lovefield

swaydb.simer.au

Technical documentation

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

www.graphengine.io/docs/manual

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

Developer

DolphinDB, Inc

Microsoft

Google

Simer Plaha

Initial release

2018

2010

2014

2018

Current release

v2.00.4, January 2022

2.1.12, February 2017

License

Commercial or Open Source

commercial

free community version available

Open Source

MIT License

Open Source

Apache 2.0

Open Source

GNU Affero GPL V3.0

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++

.NET and C

JavaScript

Scala

Server operating systems

Linux
Windows

.NET

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

tested with Chrome, Firefox, IE, Safari

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

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

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

Supported programming languages

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

C#
C++
F#
Visual Basic

JavaScript

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Administrators, Users, Groups

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More resources

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