DBMS > DolphinDB vs. Hyprcubd vs. Ingres vs. Lovefield

System Properties Comparison DolphinDB vs. Hyprcubd vs. Ingres vs. Lovefield

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Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

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.

Serverless Time Series DBMS

Well established RDBMS

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Time Series DBMS

Relational DBMS

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	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

www.dolphindb.com

hyprcubd.com (offline)

www.actian.com/databases/ingres

google.github.io/lovefield

Technical documentation

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

docs.actian.com/ingres

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

Developer

DolphinDB, Inc

Hyprcubd, Inc.

Actian Corporation

Google

Initial release

2018

1974

originally developed at University Berkely in early 1970s

2014

Current release

v2.00.4, January 2022

11.2, May 2022

2.1.12, February 2017

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Apache 2.0

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++

JavaScript

Server operating systems

Linux
Windows

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

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

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

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

gRPC (https)

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

Supported programming languages

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

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Ingres Star to access multiple databases simultaneously

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Ingres Replicator

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

Immediate 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

MVCC

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

Administrators, Users, Groups

token access

fine grained access rights according to SQL-standard

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