DBMS > AlaSQL vs. Apache Pinot vs. DolphinDB vs. Graph Engine

System Properties Comparison AlaSQL vs. Apache Pinot vs. DolphinDB vs. Graph Engine

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

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

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Graph DBMS
Key-value store

Secondary database models

Relational DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Website

Technical documentation

github.com/AlaSQL/alasql

docs.pinot.apache.org

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

www.graphengine.io/docs/manual

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation and contributors

DolphinDB, Inc

Microsoft

Initial release

2014

2015

2018

2010

Current release

1.0.0, September 2023

v2.00.4, January 2022

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2.0

commercial

free community version available

Open Source

MIT License

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

Java

C++

.NET and C

Server operating systems

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

All OS with a Java JDK11 or higher

Linux
Windows

.NET

Data scheme

schema-free

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

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

SQL-like query language

APIs and other access methods

JavaScript API

JDBC

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

RESTful HTTP API

Supported programming languages

JavaScript

Go
Java
Python

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

C#
C++
F#
Visual Basic

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

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

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

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