DBMS > AlaSQL vs. DolphinDB vs. Hyprcubd vs. Sadas Engine

System Properties Comparison AlaSQL vs. DolphinDB vs. Hyprcubd vs. Sadas Engine

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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

JavaScript DBMS library

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

alasql.org

www.dolphindb.com

hyprcubd.com (offline)

www.sadasengine.com

Technical documentation

github.com/AlaSQL/alasql

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Andrey Gershun & Mathias R. Wulff

DolphinDB, Inc

Hyprcubd, Inc.

SADAS s.r.l.

Initial release

2014

2018

2006

Current release

v2.00.4, January 2022

8.0

License

Commercial or Open Source

Open Source

MIT-License

commercial

free community version available

commercial

free trial version available

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

JavaScript

C++

Server operating systems

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

Linux
Windows

hosted

AIX
Linux
Windows

Data scheme

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL-like query language

yes

APIs and other access methods

JavaScript API

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

gRPC (https)

JDBC
ODBC
Proprietary protocol

Supported programming languages

JavaScript

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

only for local storage and DOM-storage

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

Administrators, Users, Groups

token access

Access rights for users, groups and roles according to SQL-standard

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