DBMS > DolphinDB vs. gStore vs. Memcached vs. Valentina Server

System Properties Comparison DolphinDB vs. gStore vs. Memcached vs. Valentina Server

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Editorial information provided by DB-Engines

Name

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.

A native Graph DBMS to store and maintain very large RDF datasets.

In-memory key-value store, originally intended for caching

Object-relational database and reports server

Primary database model

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	0.04
Rank	#359	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

Technical documentation

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

en.gstore.cn/#/enDocs

github.com/memcached/memcached/wiki

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

DolphinDB, Inc

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Paradigma Software

Initial release

2018

2016

2003

1999

Current release

v2.00.4, January 2022

1.2, November 2023

1.6.25, March 2024

5.7.5

License

Commercial or Open Source

commercial

free community version available

Open Source

BSD

Open Source

BSD license

commercial

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

C++

Server operating systems

Linux
Windows

Linux

FreeBSD
Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

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

SQL-like query language

yes

APIs and other access methods

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

HTTP API
SPARQL 1.1

Proprietary protocol

ODBC

Supported programming languages

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

C++
Java
JavaScript (Node.js)
PHP
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Repcached, a Memcached patch, provides this functionallity

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Users, roles and permissions, Role-Based Access Control (RBAC) supported

yes

using SASL (Simple Authentication and Security Layer) protocol

fine grained access rights according to SQL-standard

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More resources

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3 February 2014, Matthias Gelbmann

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3 October 2012, Matthias Gelbmann, Paul Andlinger

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