DBMS > AlaSQL vs. DolphinDB vs. GigaSpaces

System Properties Comparison AlaSQL vs. DolphinDB vs. GigaSpaces

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Editorial information provided by DB-Engines

Name

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.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Primary database model

Document store
Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

Values are user defined objects

Secondary database models

Relational DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Website

alasql.org

www.dolphindb.com

www.gigaspaces.com

Technical documentation

github.com/AlaSQL/alasql

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

docs.gigaspaces.com/latest/landing.html

Developer

Andrey Gershun & Mathias R. Wulff

DolphinDB, Inc

Gigaspaces Technologies

Initial release

2014

2018

2000

Current release

v2.00.4, January 2022

15.5, September 2020

License

Commercial or Open Source

Open Source

MIT-License

commercial

free community version available

Open Source

Apache Version 2; Commercial licenses available

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

JavaScript

C++

Java, C++, .Net

Server operating systems

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

Linux
Windows

Linux
macOS
Solaris
Windows

Data scheme

schema-free

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.

XML can be used for describing objects metadata

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

SQL-99 for query and DML statements

APIs and other access methods

JavaScript API

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

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

Supported programming languages

JavaScript

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

.Net
C++
Java
Python
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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

ACID

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

User concepts

Access control

Administrators, Users, Groups

Role-based access control

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