DBMS > AlaSQL vs. DolphinDB vs. etcd vs. TinkerGraph

System Properties Comparison AlaSQL vs. DolphinDB vs. etcd vs. TinkerGraph

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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.

A distributed reliable key-value store

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Document store
Relational DBMS

Time Series DBMS

Key-value store

Graph 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	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

alasql.org

www.dolphindb.com

etcd.io
github.com/etcd-io/etcd

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

github.com/AlaSQL/alasql

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

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

Developer

Andrey Gershun & Mathias R. Wulff

DolphinDB, Inc

Initial release

2014

2018

2009

Current release

v2.00.4, January 2022

3.4, August 2019

License

Commercial or Open Source

Open Source

MIT-License

commercial

free community version available

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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

JavaScript

C++

Java

Server operating systems

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

Linux
Windows

FreeBSD
Linux
Windows

experimental

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.

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

gRPC
JSON over HTTP

TinkerPop 3

Supported programming languages

JavaScript

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

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Groovy
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

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

none

Foreign keys

Referential integrity

yes

Relationships in graphs

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

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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